Taghi M. Khoshgoftaar

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RUSBoost: Improving classification performance when training data is skewed

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 19th International Conference on Pattern Recognition.

Evolutionary Optimization of Software Quality Modeling with Multiple Repositories

Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya, 2010, IEEE Transactions on Software Engineering.

Proceedings of the 9th [i. e. 12th] IASTED International Conference on Software Engineering and Applications, November 16-18, 2008, Orland, Florida, USA

Taghi M. Khoshgoftaar, 2008 .

Predicting Software Development Errors Using Software Complexity Metrics

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1990, IEEE J. Sel. Areas Commun..

Exploring filter-based feature selection techniques for software quality classification

Taghi M. Khoshgoftaar, Kehan Gao, Huanjing Wang, 2012, Int. J. Inf. Decis. Sci..

A Comparative Study on the Stability of Software Metric Selection Techniques

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2012, 2012 11th International Conference on Machine Learning and Applications.

Investigation of Maxout Activations on Convolutional Neural Networks for Big Data Text Sentiment Analysis

Taghi M. Khoshgoftaar, Paul Morris, Gabriel Castaneda Oscos, 2019, FLAIRS.

Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction

Taghi M. Khoshgoftaar, Xiaoyuan Su, Xingquan Zhu, 2007, ISVC.

Evaluating indirect and direct classification techniques for network intrusion detection

Taghi M. Khoshgoftaar, Kehan Gao, Nawal H. Ibrahim, 2005, Intell. Data Anal..

Comparing Feature Selection Techniques for Software Quality Estimation Using Data-Sampling-Based Boosting Algorithms

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2015 .

An Empirical Study on the Stability of Feature Selection for Imbalanced Software Engineering Data

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2012, 2012 11th International Conference on Machine Learning and Applications.

lVlo deling Fault -Yrone

Taghi M. Khoshgoftaar, Edward B. Allen, Vishal Thaker, 2000 .

Predicting sentinel node status in melanoma from a real-world EHR dataset

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Comparison of Data Sampling Approaches for Imbalanced Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2014, FLAIRS.

Software quality classification modeling using the SPRINT decision tree algorithm

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2002, 14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings..

An Information Theory-Based Approach to Quantifying the Contribution of a Software Metric

Taghi M. Khoshgoftaar, Edward B. Allen, David L. Lanning, 1997, J. Syst. Softw..

Wrapper-Based Feature Ranking for Software Engineering Metrics

Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano, 2009, 2009 International Conference on Machine Learning and Applications.

Using Classification Trees for Software Quality Models: Lessons Learned

Taghi M. Khoshgoftaar, Edward B. Allen, Archana Naik, 1999, Int. J. Softw. Eng. Knowl. Eng..

An empirical study of program quality during testing and maintenance

Taghi M. Khoshgoftaar, Robert M. Szabo, Timothy G. Woodcock, 2004, Software Quality Journal.

A Dynamometer for an Ocean Turbine Prototype: Reliability through Automated Monitoring

Taghi M. Khoshgoftaar, Bassem Alhalabi, Janell Duhaney, 2011, 2011 IEEE 13th International Symposium on High-Assurance Systems Engineering.

Noise Correction using Bayesian Multiple Imputation

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

Classification of Ships in Surveillance Video

Taghi M. Khoshgoftaar, Andres Folleco, Qiming Luo, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

Optimizing Wrapper-Based Feature Selection for Use on Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2014, FLAIRS.

Using Classifier-Based Nominal Imputation to Improve Machine Learning

Taghi M. Khoshgoftaar, Amri Napolitano, Xiaoyuan Su, 2011, PAKDD.

Predicting fault-prone modules with case-based reasoning

Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, 1997, Proceedings The Eighth International Symposium on Software Reliability Engineering.

Improving neural network predictions of software quality using principal components analysis

Taghi M. Khoshgoftaar, R. M. Szabo, R. M. Szabo, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

The use of software complexity metrics in software reliability modeling

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1991, Proceedings. 1991 International Symposium on Software Reliability Engineering.

Estimating Outlier Score Probabilities

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

Can neural networks be easily interpreted in software cost estimation?

Taghi M. Khoshgoftaar, Alain Abran, Ali Idri, 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

An Empirical Study of Predictive Modeling Techniques of Software Quality

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2010, BIONETICS.

Evaluating Model Predictive Performance: A Medicare Fraud Detection Case Study

Taghi M. Khoshgoftaar, Richard A. Bauder, Matthew Herland, 2019, 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI).

Deep Learning with Maxout Activations for Visual Recognition and Verification

Taghi M. Khoshgoftaar, Gabriel Castaneda Oscos, Paul Morris, 2019, 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI).

Survey of review spam detection using machine learning techniques

Taghi M. Khoshgoftaar, Joseph D. Prusa, Aaron N. Richter, 2015, Journal of Big Data.

Hierarchical indexing of ocean survey video by mean shift clustering and MDL principle

Taghi M. Khoshgoftaar, Qiming Luo, Edgar An, 2005, IRI -2005 IEEE International Conference on Information Reuse and Integration, Conf, 2005..

NEURAL NETWORKS FOR SOFTWARE QUALITY PREDICTION

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1998 .

Exploring the Effectiveness of Twitter at Polling the United States 2016 Presidential Election

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2017, 2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC).

Ensemble Feature Selection Technique for Software Quality Classification

Taghi M. Khoshgoftaar, Kehan Gao, Huanjing Wang, 2010, International Conference on Software Engineering and Knowledge Engineering.

The Use of Ensemble-Based Data Preprocessing Techniques for Software Defect Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2014, Int. J. Softw. Eng. Knowl. Eng..

Addressing Class Imbalance in Non-binary Classification Problems

Taghi M. Khoshgoftaar, Zhiwei Xu, Naeem Seliya, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

PREDICTING SOFTWARE QUALITY, DURING TESTING, USING NEURAL NETWORK MODELS: A COMPARATIVE STUDY

Taghi M. Khoshgoftaar, Robert M. Szabo, R. M. Szabo, 1994 .

Empirical Bayes methods in time series analysis

Taghi M. Khoshgoftaar, 1982 .

CREATING ENTREPRENEURIAL UNIVERSITY

Taghi M. Khoshgoftaar, Ankur Agarwal, Shihong Huang, 2013 .

Predictive modeling of software quality for very large telecommunications systems

Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, 1996, Proceedings of ICC/SUPERCOMM '96 - International Conference on Communications.

An Empirical Study of Feature Ranking Techniques for Software Quality Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2012, Int. J. Softw. Eng. Knowl. Eng..

Which Software Modules have Faults which will be Discovered by Customers?

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999, J. Softw. Maintenance Res. Pract..

Detection of Phishing Webpages Using Heterogeneous Transfer Learning

Taghi M. Khoshgoftaar, Karl R. Weiss, 2017, 2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC).

Exploring the behaviour of neural network software quality models

Taghi M. Khoshgoftaar, Robert M. Szabo, Peter J. Guasti, 1995, Softw. Eng. J..

Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, 2007, IRI.

A survey of transfer learning

Taghi M. Khoshgoftaar, Karl R. Weiss, Dingding Wang, 2016, Journal of Big Data.

Detection of software modules with high debug code churn in a very large legacy system

Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, 1996, Proceedings of ISSRE '96: 7th International Symposium on Software Reliability Engineering.

Software Quality Analysis of Unlabeled Program Modules With Semisupervised Clustering

Taghi M. Khoshgoftaar, Naeem Seliya, 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

Choosing an Appropriate Ensemble Classifier for Balanced Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

Software Module Risk Analysis

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2007, Wiley Encyclopedia of Computer Science and Engineering.

Regression modelling of software quality: empirical investigation☆

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1990 .

Arbitrarily-Shaped Window Based Stereo Matching using the Go-Light Optimization Algorithm

Taghi M. Khoshgoftaar, Xiaoyuan Su, T. Khoshgoftaar, 2007, 2007 IEEE International Conference on Image Processing.

Assessments of Feature Selection Techniques with Respect to Data Sampling for Highly Imbalanced Software Measurement Data

Taghi M. Khoshgoftaar, Kehan Gao, 2015 .

Big Data fraud detection using multiple medicare data sources

Taghi M. Khoshgoftaar, Richard A. Bauder, Matthew Herland, 2018, J. Big Data.

Deep Learning Techniques in Big Data Analytics

Taghi M. Khoshgoftaar, Naeem Seliya, Randall Wald, 2016, Big Data Technologies and Applications.

Tree-Based Software Quality Classification Using Genetic Programming

Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya, 2006 .

Detecting program modules with low testability

Taghi M. Khoshgoftaar, Jeffrey M. Voas, Robert M. Szabo, 1995, Proceedings of International Conference on Software Maintenance.

Value-Based Software Quality Modeling

Taghi M. Khoshgoftaar, Naeem Seliya, 2009, SEKE.

Ensemble Feature Ranking Methods for Data Intensive Computing Applications

Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse, 2011 .

Combining Feature Selection and Ensemble Learning for Software Quality Estimation

Taghi M. Khoshgoftaar, Kehan Gao, Randall Wald, 2014, FLAIRS Conference.

Gene selection stability's dependence on dataset difficulty

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

A review of the stability of feature selection techniques for bioinformatics data

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

Investigating Transfer Learners for Robustness to Domain Class Imbalance

Taghi M. Khoshgoftaar, Karl R. Weiss, T. Khoshgoftaar, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

A survey on heterogeneous transfer learning

Taghi M. Khoshgoftaar, Oscar Day, T. Khoshgoftaar, 2017, Journal of Big Data.

Panel: Using information re-use and integration principles in big data

Elisa Bertino, Stuart Harvey Rubin, Taghi M. Khoshgoftaar, 2012, IRI.

MODELING SOFTWARE QUALITY WITH CLASSIFICATION TREES

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 2001 .

Learning with limited minority class data

Taghi M. Khoshgoftaar, Amri Napolitano, Andres Folleco, 2007, ICMLA 2007.

Resource-oriented software quality classification models

Taghi M. Khoshgoftaar, Naeem Seliya, Angela Herzberg, 2005, J. Syst. Softw..

Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2005, Intell. Data Anal..

A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data

Taghi M. Khoshgoftaar, Aaron N. Richter, Sara Landset, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

Examining characteristics of predictive models with imbalanced big data

Taghi M. Khoshgoftaar, Naeem Seliya, Tawfiq Hasanin, 2019, Journal of Big Data.

Impact of Feature Selection Techniques for Tweet Sentiment Classification

Taghi M. Khoshgoftaar, Joseph D. Prusa, David J. Dittman, 2015, FLAIRS.

Is Data Sampling Required When Using Random Forest for Classification on Imbalanced Bioinformatics Data?

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2016, Theoretical Information Reuse and Integration.

Identifying noise in an attribute of interest

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

Skewed Class Distributions and Mislabeled Examples

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2007 .

Efficient image segmentation by mean shift clustering and MDL-guided region merging

Taghi M. Khoshgoftaar, Qiming Luo, T. Khoshgoftaar, 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

A Procedure for Collecting and Labeling Man-in-the-Middle Attack Traffic

Taghi M. Khoshgoftaar, Maryam M. Najafabadi, Chad Calvert, 2017 .

Improving software quality estimation by combining feature selection strategies with sampled ensemble learning

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

The use of balance-aware subsampling for bioinformatics datasets

Taghi M. Khoshgoftaar, Randall Wald, Alireza Fazelpour, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

An application of a rule-based model in software quality classification

Taghi M. Khoshgoftaar, Kehan Gao, Lofton A. Bullard, 2007, ICMLA 2007.

Emerald: Software Metrics and Models on the Desktop

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1996, IEEE Softw..

Data Intensive Computing: A Biomedical Case Study in Gene Selection and Filtering

Taghi M. Khoshgoftaar, Imad Mahgoub, Xingquan Zhu, 2011 .

Neural network application in support of software reliability engineering

Abhijit S. Pandya, Taghi M. Khoshgoftaar, David L. Lanning, 1995, SPIE Defense + Commercial Sensing.

Tree-based software quality estimation models for fault prediction

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

Stability Analysis of Feature Ranking Techniques on Biological Datasets

Taghi M. Khoshgoftaar, Huanjing Wang, Randall Wald, 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine.

Feature list aggregation approaches for ensemble gene selection on patient response datasets

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

Deep Neural Network Architecture for Character-Level Learning on Short Text

Taghi M. Khoshgoftaar, Joseph D. Prusa, 2017, FLAIRS Conference.

A Comparative Study of Ordering and Classification of Fault-Prone Software Modules

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1999, Empirical Software Engineering.

Data Mining of Software Development Databases

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 2004, Software Quality Journal.

Designing a Testing Framework for Transfer Learning Algorithms (Application Paper)

Taghi M. Khoshgoftaar, Karl R. Weiss, Oneeb Rehman, 2016, 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI).

Balancing Misclassification Rates in Classification-Tree Models of Software Quality

Taghi M. Khoshgoftaar, Edward B. Allen, Xiaojing Yuan, 2004, Empirical Software Engineering.

Controlling overfitting in software quality models: experiments with regression trees and classification

Taghi M. Khoshgoftaar, Edward B. Allen, Jianyu Deng, 2001, Proceedings Seventh International Software Metrics Symposium.

Detecting Slow HTTP POST DoS Attacks Using Netflow Features

Taghi M. Khoshgoftaar, Maryam M. Najafabadi, Chad Calvert, 2019, FLAIRS.

Location-Based Twitter Sentiment Analysis for Predicting the U.S. 2016 Presidential Election

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2018, FLAIRS Conference.

The Effects of Random Undersampling with Simulated Class Imbalance for Big Data

Taghi M. Khoshgoftaar, Tawfiq Hasanin, T. Khoshgoftaar, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

Semi-supervised learning for software quality estimation

Taghi M. Khoshgoftaar, Naeem Seliya, Shi Zhong, 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

A neural network approach for predicting software development faults

Abhijit S. Pandya, Taghi M. Khoshgoftaar, Hemant B. More, 1992, [1992] Proceedings Third International Symposium on Software Reliability Engineering.

A performance analysis of an object-based I/O architecture in a video server environment

Taghi M. Khoshgoftaar, Khoa D. Huynh, T. Khoshgoftaar, 1995, Multimedia Systems.

Should the Same Learners Be Used Both within Wrapper Feature Selection and for Building Classification Models?

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

Fourier transforms for vibration analysis: A review and case study

Taghi M. Khoshgoftaar, Randall Wald, John C. Sloan, 2011, 2011 IEEE International Conference on Information Reuse & Integration.

Aggregating performance metrics for classifier evaluation

Taghi M. Khoshgoftaar, Jason Van Hulse, Naeem Seliya, 2009, 2009 IEEE International Conference on Information Reuse & Integration.

VoB predictors: Voting on bagging classifications

Taghi M. Khoshgoftaar, Xiaoyuan Su, Xingquan Zhu, 2008, 2008 19th International Conference on Pattern Recognition.

Software Fault Imputation in Noisy and Incomplete Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco, 2008 .

Feature Selection for Highly Imbalanced Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Kehan Gao, 2012 .

Preparing measurements of legacy software for predicting operational faults

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999, Proceedings IEEE International Conference on Software Maintenance - 1999 (ICSM'99). 'Software Maintenance for Business Change' (Cat. No.99CB36360).

Aggregating Data Sampling with Feature Subset Selection to Address Skewed Software Defect Data

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2015, Int. J. Softw. Eng. Knowl. Eng..

Selecting the Appropriate Data Sampling Approach for Imbalanced and High-Dimensional Bioinformatics Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

A comparative study of predictive models for program changes during system testing and maintenance

Taghi M. Khoshgoftaar, John C. Munson, David L. Lanning, 1993, 1993 Conference on Software Maintenance.

Survey on deep learning with class imbalance

Taghi M. Khoshgoftaar, Justin M. Johnson, Justin M. Johnson, 2019, J. Big Data.

Assuring Timeliness in an e-Science Service-Oriented Architecture

Taghi M. Khoshgoftaar, John C. Sloan, Venkat Raghav, 2008, Computer.

The Effect of Number of Iterations on Ensemble Gene Selection

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2012, 2012 11th International Conference on Machine Learning and Applications.

Multiple Imputation of Software Measurement Data: A Case Study

Taghi M. Khoshgoftaar, Jason Van Hulse, 2006, SEKE.

A Comparative Study of Data Sampling and Cost Sensitive Learning

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 IEEE International Conference on Data Mining Workshops.

Improving code churn predictions during the system test and maintenance phases

Taghi M. Khoshgoftaar, Robert M. Szabo, R. M. Szabo, 1994, Proceedings 1994 International Conference on Software Maintenance.

Evaluation of maxout activations in deep learning across several big data domains

Taghi M. Khoshgoftaar, Paul Morris, Gabriel Castaneda, 2019, Journal of Big Data.

A System-Level Modeling Methodology for Performance-Driven Component Selection in Multicore Architectures

Taghi M. Khoshgoftaar, Ankur Agarwal, Georgiana L. Hamza-Lup, 2012, IEEE Systems Journal.

CatBoost for big data: an interdisciplinary review

Taghi M. Khoshgoftaar, John T. Hancock, 2020, J. Big Data.

The Effect of Data Sampling When Using Random Forest on Imbalanced Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

Using evolutionary sampling to mine imbalanced data

Taghi M. Khoshgoftaar, Ramaswamy Narayanan, D. J. Drown, 2007, ICMLA 2007.

Low-Effort Labeling of Network Events for Intrusion Detection in WLANs

Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya, 2008, Int. J. Artif. Intell. Tools.

Modeling the relationship between source code complexity and maintenance difficulty

Taghi M. Khoshgoftaar, David L. Lanning, T. Khoshgoftaar, 1994, Computer.

OCEAN TURBINES — A RELIABILITY ASSESSMENT

Taghi M. Khoshgoftaar, Frederick R. Driscoll, John C. Sloan, 2009 .

Introduction to the Special Issue on Quality Engineering with Computational Intelligence

Taghi M. Khoshgoftaar, 2004, Software Quality Journal.

Mean Aggregation versus Robust Rank Aggregation for Ensemble Gene Selection

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2012, 2012 11th International Conference on Machine Learning and Applications.

Using Random Undersampling to Alleviate Class Imbalance on Tweet Sentiment Data

Taghi M. Khoshgoftaar, Amri Napolitano, Joseph D. Prusa, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

Fraud Detection with a Limited Number of Known Fraudulent Medicare Providers

Taghi M. Khoshgoftaar, Amri Napolitano, Richard A. Bauder, 2018, The Florida AI Research Society.

Modeling software quality: the Software Measurement Analysis and Reliability Toolkit

Taghi M. Khoshgoftaar, Edward B. Allen, Jason C. Busboom, 2000, Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000.

Enhancing Ensemble Learners with Data Sampling on High-Dimensional Imbalanced Tweet Sentiment Data

Taghi M. Khoshgoftaar, Naeem Seliya, Joseph D. Prusa, 2016, FLAIRS.

Analyzing the Impact of Attribute Noise on Software Quality Classification

Taghi M. Khoshgoftaar, Andres Folleco, Lofton A. Bullard, 2008, SEKE.

Modelling software quality with GP

Taghi M. Khoshgoftaar, Edward B. Allen, Matthew P. Evett, 1999, GECCO.

Using Feature Selection in Combination with Ensemble Learning Techniques to Improve Tweet Sentiment Classification Performance

Taghi M. Khoshgoftaar, Amri Napolitano, Joseph D. Prusa, 2015, 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI).

Comparing Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2014, SEKE.

Data Mining for Predictors of Software Quality

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999, Int. J. Softw. Eng. Knowl. Eng..

The impact of costs of misclassification on software quality modeling

Taghi M. Khoshgoftaar, Edward B. Allen, 1997, Proceedings Fourth International Software Metrics Symposium.

Assessing uncertain predictions of software quality

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999, Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403).

Editorial: Special issue on mining low-quality data

Taghi M. Khoshgoftaar, Ian Davidson, Shichao Zhang, 2007, Knowledge and Information Systems.

Stability of Filter-Based Feature Selection Methods for Imbalanced Software Measurement Data

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2012, SEKE.

A survey on Image Data Augmentation for Deep Learning

Taghi M. Khoshgoftaar, Connor Shorten, T. Khoshgoftaar, 2019, Journal of Big Data.

Medical Provider Specialty Predictions for the Detection of Anomalous Medicare Insurance Claims

Taghi M. Khoshgoftaar, Richard A. Bauder, Matthew Herland, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

Studying the Effect of Class Imbalance in Ocean Turbine Fault Data on Reliable State Detection

Taghi M. Khoshgoftaar, Amri Napolitano, Janell Duhaney, 2012, 2012 11th International Conference on Machine Learning and Applications.

A clustering approach to wireless network intrusion detection

Taghi M. Khoshgoftaar, Shi Zhong, Shyam Varan Nath, 2005, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05).

Fusing Wavelet Features for Ocean Turbine Fault Detection

Taghi M. Khoshgoftaar, Randall Wald, Janell Duhaney, 2016 .

Multi-Objective Optimization by CBR GA-Optimizer for Module-Order Modeling

Taghi M. Khoshgoftaar, Kehan Gao, Yudong Xiao, 2004, SEKE.

RUDY Attack: Detection at the Network Level and Its Important Features

Taghi M. Khoshgoftaar, Amri Napolitano, Maryam M. Najafabadi, 2016, FLAIRS.

Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures

Taghi M. Khoshgoftaar, Joseph D. Prusa, Ryan Sagul, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

Determining the Number of Iterations Appropriate for Ensemble Gene Selection on Microarray Data

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 11th International Conference on Machine Learning and Applications.

First Order Statistics Based Feature Selection: A Diverse and Powerful Family of Feature Seleciton Techniques

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2012, 2012 11th International Conference on Machine Learning and Applications.

Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction

Taghi M. Khoshgoftaar, Xingquan Zhu, Chinar C. Shah, 2008, FLAIRS.

Software Quality Classification Modeling Using the SPRINT Decision Tree Algorithm

Taghi M. Khoshgoftaar, Naeem Seliya, 2003, Int. J. Artif. Intell. Tools.

A Session Based Approach for Aggregating Network Traffic Data -- The SANTA Dataset

Taghi M. Khoshgoftaar, Maryam M. Najafabadi, Charles Wheelus, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

Investigating ARIMA models of software system quality

Taghi M. Khoshgoftaar, Robert M. Szabo, R. M. Szabo, 1995, Software Quality Journal.

Which software modules have faults which will be discovered by customers

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999 .

A New Fixed-Overlap Partitioning Algorithm for Determining Stability of Bioinformatics Gene Rankers

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2012, 2012 11th International Conference on Machine Learning and Applications.

Machine prediction of personality from Facebook profiles

Taghi M. Khoshgoftaar, Randall Wald, Chris Sumner, 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

Software reliability engineering with genetic programming

Taghi M. Khoshgoftaar, Yi Liu, 2003 .

A practical classification-rule for software-quality models

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 2000, IEEE Trans. Reliab..

Dynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software

Taghi M. Khoshgoftaar, Lianfen Qian, Qingchuan Yao, 2010, J. Softw. Eng. Appl..

Classification performance of three approaches for combining data sampling and gene selection on bioinformatics data

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

Maxout Neural Network for Big Data Medical Fraud Detection

Taghi M. Khoshgoftaar, Gabriel Castaneda Oscos, Paul Morris, 2019, 2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService).

Investigating Random Undersampling and Feature Selection on Bioinformatics Big Data

Taghi M. Khoshgoftaar, Naeem Seliya, Tawfiq Hasanin, 2019, 2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService).

How Many Software Metrics Should be Selected for Defect Prediction?

Taghi M. Khoshgoftaar, Naeem Seliya, Huanjing Wang, 2011, FLAIRS.

Generating multiple noise elimination filters with the ensemble-partitioning filter

Taghi M. Khoshgoftaar, Pierre Rebours, T. Khoshgoftaar, 2004, Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004..

Can metrics and models be applied across multiple releases or projects?

Taghi M. Khoshgoftaar, Norman F. Schneidewind, George E. Stark, 1999, Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403).

The effects of class rarity on the evaluation of supervised healthcare fraud detection models

Taghi M. Khoshgoftaar, Richard A. Bauder, Matthew Herland, 2019, J. Big Data.

Software Quality Modeling with Limited Apriori Defect Data

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2009 .

Predicting fault-prone software modules in embedded systems with classification trees

Taghi M. Khoshgoftaar, Edward B. Allen, 1999, Proceedings 4th IEEE International Symposium on High-Assurance Systems Engineering.

Modeling fault-prone modules of subsystems

Taghi M. Khoshgoftaar, Edward B. Allen, Vishal Thaker, 2000, Proceedings 11th International Symposium on Software Reliability Engineering. ISSRE 2000.

Rotation invariant face recognition survey

Taghi M. Khoshgoftaar, Randall Wald, Gabriel Castaneda Oscos, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

A parallel and distributed stochastic gradient descent implementation using commodity clusters

Taghi M. Khoshgoftaar, Flavio Villanustre, Robert K. L. Kennedy, 2019, Journal of Big Data.

Random Forest with 200 Selected Features: An Optimal Model for Bioinformatics Research

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 12th International Conference on Machine Learning and Applications.

Evolutionary neural networks: a robust approach to software reliability problems

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1997, Proceedings The Eighth International Symposium on Software Reliability Engineering.

A Comprehensive Empirical Study of Count Models for Software Fault Prediction

Taghi M. Khoshgoftaar, Kehan Gao, T. Khoshgoftaar, 2007, IEEE Transactions on Reliability.

A survey and analysis of intrusion detection models based on CSE-CIC-IDS2018 Big Data

Taghi M. Khoshgoftaar, Joffrey L. Leevy, T. Khoshgoftaar, 2020, J. Big Data.

Mining Data with Rare Events: A Case Study

Taghi M. Khoshgoftaar, Amri Napolitano, C. Seiffert, 2007 .

Select-Bagging: Effectively Combining Gene Selection and Bagging for Balanced Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

Can a software quality model hit a moving target?

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1998, Proceedings. International Conference on Software Maintenance (Cat. No. 98CB36272).

Random forest: A reliable tool for patient response prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

Big Data: Deep Learning for financial sentiment analysis

Taghi M. Khoshgoftaar, Dingding Wang, Sahar Sohangir, 2018, Journal of Big Data.

Comparative Analysis on the Stability of Feature Selection Techniques Using Three Frameworks on Biological Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 12th International Conference on Machine Learning and Applications.

Observing the Effect of the Choice of Classifier on Bioinformatics Data with Varying Levels of Data Quality and Class Balance

Taghi M. Khoshgoftaar, David J. Dittman, Alireza Fazelpour, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

The effect of measurement approach and noise level on gene selection stability

Taghi M. Khoshgoftaar, Randall Wald, Ahmad Abu Shanab, 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine.

Evolutionary data analysis for the class imbalance problem

Taghi M. Khoshgoftaar, Naeem Seliya, D. J. Drown, 2010, Intell. Data Anal..

Estimating software project effort by analogy based on linguistic values

Taghi M. Khoshgoftaar, Alain Abran, Ali Idri, 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

Improving Software-Quality Predictions With Data Sampling and Boosting

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

A Case Studv in Telecommunications

Taghi M. Khoshgoftaar, Edward B. Allen, 1996 .

Imputation techniques for multivariate missingness in software measurement data

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2008, Software Quality Journal.

Measuring robustness of Feature Selection techniques on software engineering datasets

Taghi M. Khoshgoftaar, Huanjing Wang, Randall Wald, 2011, 2011 IEEE International Conference on Information Reuse & Integration.

Rough set-based software quality models and quality of data

Taghi M. Khoshgoftaar, Lofton A. Bullard, 2008 .

Choosing software metrics for defect prediction: an investigation on feature selection techniques

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2011, Softw. Pract. Exp..

A Novel Noise-Resistant Boosting Algorithm for Class-Skewed Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2012, 2012 11th International Conference on Machine Learning and Applications.

Unsupervised multiscale color image segmentation based on MDL principle

Taghi M. Khoshgoftaar, Qiming Luo, T. Khoshgoftaar, 2006, IEEE Transactions on Image Processing.

EMERALD: software metrics and models on the desktop

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1996, Proceedings of the Fourth International Symposium on Assessment of Software Tools.

Investigating Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2015, Int. J. Softw. Eng. Knowl. Eng..

An Empirical Study on Wrapper-Based Feature Ranking

Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse, 2009, 2009 21st IEEE International Conference on Tools with Artificial Intelligence.

A Novel Hybrid Search Algorithm for Feature Selection

Taghi M. Khoshgoftaar, Huanjing Wang, Pengpeng Lin, 2009, International Conference on Software Engineering and Knowledge Engineering.

A Text Mining Approach for Anomaly Detection in Application Layer DDoS Attacks

Taghi M. Khoshgoftaar, Maryam M. Najafabadi, Chad Calvert, 2017, FLAIRS Conference.

Developing an Effective Validation Strategy for Genetic Programming Models Based on Multiple Datasets

Taghi M. Khoshgoftaar, Yi Liu, Jenq-Foung Yao, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

Comparing Two New Gene Selection Ensemble Approaches with the Commonly-Used Approach

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 11th International Conference on Machine Learning and Applications.

A review of statistical and machine learning methods for modeling cancer risk using structured clinical data

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2018, Artif. Intell. Medicine.

A neural network modeling methodology for the detection of high-risk programs

Abhijit S. Pandya, Taghi M. Khoshgoftaar, David L. Lanning, 1993, Proceedings of 1993 IEEE International Symposium on Software Reliability Engineering.

Improving usefulness of software quality classification models based on Boolean discriminant functions

Taghi M. Khoshgoftaar, T. Khoshgoftaar, 2002, 13th International Symposium on Software Reliability Engineering, 2002. Proceedings..

Exploring Ensemble-Based Data Preprocessing Techniques for Software Quality Estimation

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2013, SEKE.

Skewed Class Distributions and Mislabeled Examples

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

A performance analysis of the IBM subsystem control block architecture in a video conferencing environment

Taghi M. Khoshgoftaar, Khoa D. Huynh, 1993, MULTIMEDIA '93.

Comparison of Stability for Different Families of Filter-Based and Wrapper-Based Feature Selection

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 12th International Conference on Machine Learning and Applications.

Measurement of data structure complexity

Taghi M. Khoshgoftaar, John C. Munson, 1993, J. Syst. Softw..

A Survey of Medicare Data Processing and Integration for Fraud Detection

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

An application of fuzzy clustering to software quality prediction

Taghi M. Khoshgoftaar, K. Ganesan, Edward B. Allen, 2000, Proceedings 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology.

Building an Effective Classification Model for Breast Cancer Patient Response Data

Taghi M. Khoshgoftaar, David J. Dittman, Brian Heredia, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

A novel feature selection technique for highly imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Kehan Gao, 2010, 2010 IEEE International Conference on Information Reuse & Integration.

Impact of Data Sampling on Stability of Feature Selection for Software Measurement Data

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

On the impact of software product dissimilarity on software quality models

Taghi M. Khoshgoftaar, David L. Lanning, T. Khoshgoftaar, 1994, Proceedings of 1994 IEEE International Symposium on Software Reliability Engineering.

Deep learning applications and challenges in big data analytics

Taghi M. Khoshgoftaar, Naeem Seliya, Randall Wald, 2015, Journal of Big Data.

Cost-sensitive boosting in software quality modeling

Taghi M. Khoshgoftaar, Laurent A. Nguyen, Lofton A. Bullard, 2002, 7th IEEE International Symposium on High Assurance Systems Engineering, 2002. Proceedings..

Mining Data with Rare Events: A Case Study

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

A Framework of Combining Data Pre-Processing Methods and Boosting for Software Quality Classification

Taghi M. Khoshgoftaar, 2015 .

Software quality assessment using a multi-strategy classifier

Taghi M. Khoshgoftaar, Kehan Gao, Yudong Xiao, 2014, Inf. Sci..

Attribute Selection and Imbalanced Data: Problems in Software Defect Prediction

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

Investigating class rarity in big data

Taghi M. Khoshgoftaar, Tawfiq Hasanin, Joffrey L. Leevy, 2020, Journal of Big Data.

Transfer Learning Techniques

Taghi M. Khoshgoftaar, Karl R. Weiss, Dingding Wang, 2016, Big Data Technologies and Applications.

An Empirical Evaluation of Repetitive Undersampling Techniques

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2010, Int. J. Softw. Eng. Knowl. Eng..

Evolutionary Sampling and Software Quality Modeling of High-Assurance Systems

Taghi M. Khoshgoftaar, Naeem Seliya, D. J. Drown, 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

Identification of fuzzy models of software cost estimation

Taghi M. Khoshgoftaar, Zhiwei Xu, T. Khoshgoftaar, 2004, Fuzzy Sets Syst..

Supervised Neural Network Modeling: An Empirical Investigation Into Learning From Imbalanced Data With Labeling Errors

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2010, IEEE Transactions on Neural Networks.

The Detection of Medicare Fraud Using Machine Learning Methods with Excluded Provider Labels

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2018, FLAIRS.

A Comparison of Performance Metrics with Severely Imbalanced Network Security Big Data

Taghi M. Khoshgoftaar, Tawfiq Hasanin, Joffrey L. Leevy, 2019, 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI).

A performance analysis of advanced I/O architectures for PC-based network file servers

Taghi M. Khoshgoftaar, Khoa D. Huynh, 1994, Distributed Syst. Eng..

Medicare fraud detection using neural networks

Taghi M. Khoshgoftaar, Justin M. Johnson, T. Khoshgoftaar, 2019, Journal of Big Data.

A workload model for frame-based real-time applications on distributed systems

Taghi M. Khoshgoftaar, Eduardo B. Fernández, Khoa D. Huynh, 1992, J. Syst. Softw..

Evaluating the impact of data quality on sampling

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2010, 2010 IEEE International Conference on Information Reuse & Integration.

A neural network approach for early detection of program modules having high risk in the maintenance phase

Taghi M. Khoshgoftaar, David L. Lanning, T. Khoshgoftaar, 1995, J. Syst. Softw..

Feature Selection on Dynamometer Data for Reliability Analysis

Taghi M. Khoshgoftaar, Janell Duhaney, John C. Sloan, 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

Fuzzy case-based reasoning models for software cost estimation

Taghi M. Khoshgoftaar, Alain Abran, Ali Idri, 2004 .

Investigating New Bootstrapping Approaches of Bagging Classifiers to Account for Class Imbalance in Bioinformatics Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Dynamic system complexity

Taghi M. Khoshgoftaar, John C. Munson, David L. Lanning, 1993, [1993] Proceedings First International Software Metrics Symposium.

Noise Elimination with Ensemble-Classifier Filtering: A Case-Study in Software Quality Engineerin

Taghi M. Khoshgoftaar, Vedang H. Joshi, 2004, SEKE.

A Study on the Relationships of Classifier Performance Metrics

Taghi M. Khoshgoftaar, Jason Van Hulse, Naeem Seliya, 2009, 2009 21st IEEE International Conference on Tools with Artificial Intelligence.

A Survey of Collaborative Filtering Techniques

Taghi M. Khoshgoftaar, Xiaoyuan Su, T. Khoshgoftaar, 2009, Adv. Artif. Intell..

Video and image analysis using statistical and machine learning techniques

Taghi M. Khoshgoftaar, Qiming Luo, 2007 .

Noise identification with the k-means algorithm

Taghi M. Khoshgoftaar, Wei Tang, Wei Tang, 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

Overcoming Big Data Challenges

Taghi M. Khoshgoftaar, T. Khoshgoftaar, 2013, International Conference on Software Engineering and Knowledge Engineering.

Software reliability model selection: a cast study

Taghi M. Khoshgoftaar, Timothy G. Woodcock, 1991, Proceedings. 1991 International Symposium on Software Reliability Engineering.

Evaluation of the importance of data pre-processing order when combining feature selection and data sampling

Taghi M. Khoshgoftaar, Jason Van Hulse, Randall Wald, 2012, Int. J. Bus. Intell. Data Min..

Hidden dependencies between class imbalance and difficulty of learning for bioinformatics datasets

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

Feature Selection for Optimization of Wavelet Packet Decomposition in Reliability Analysis of Systems

Taghi M. Khoshgoftaar, Randall Wald, John C. Sloan, 2013, Int. J. Artif. Intell. Tools.

Comparison of Four Performance Metrics for Evaluating Sampling Techniques for Low Quality Class-Imbalanced Data

Taghi M. Khoshgoftaar, Amri Napolitano, Andres Folleco, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

Class noise detection using frequent itemsets

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2006, Intell. Data Anal..

The use of decision trees for cost‐sensitive classification: an empirical study in software quality prediction

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2011, Wiley Interdiscip. Rev. Data Min. Knowl. Discov..

Fault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2003, Empirical Software Engineering.

Severely imbalanced Big Data challenges: investigating data sampling approaches

Taghi M. Khoshgoftaar, Richard A. Bauder, Tawfiq Hasanin, 2019, Journal of Big Data.

ATTRIBUTE NOISE DETECTION USING MULTI-RESOLUTION ANALYSIS

Taghi M. Khoshgoftaar, Andres Folleco, 2006 .

Measuring coupling and cohesion: an information-theory approach

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1999, Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403).

Assessment of a New Three-Group Software Quality Classification Technique: An Empirical Case Study

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2005, Empirical Software Engineering.

LOGISTIC REGRESSION MODELING OF SOFTWARE QUALITY

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1999 .

An empirical study of the classification performance of learners on imbalanced and noisy software quality data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2014, Inf. Sci..

Social media for polling and predicting United States election outcome

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2018, Social Network Analysis and Mining.

Editorial

Taghi M. Khoshgoftaar, Xingquan Zhu, 2013, Int. J. Artif. Intell. Tools.

Performance analysis of advanced I/O architectures for PC-based video servers

Taghi M. Khoshgoftaar, Khoa D. Huynh, T. Khoshgoftaar, 1994, Multimedia Systems.

User Behavior Anomaly Detection for Application Layer DDoS Attacks

Taghi M. Khoshgoftaar, Maryam M. Najafabadi, Chad Calvert, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

Imputed Neighborhood Based Collaborative Filtering

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

Improving Software Quality Prediction by Noise Filtering Techniques

Taghi M. Khoshgoftaar, Pierre Rebours, T. Khoshgoftaar, 2007, Journal of Computer Science and Technology.

Empirical Assessment of a Software Metric: The Information Content of Operators

Taghi M. Khoshgoftaar, Edward B. Allen, 2004, Software Quality Journal.

An Empirical Study of Software Metric Selection Techniques for Defect Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2012, SEKE.

Module-order modeling using an evolutionary multi-objective optimization approach

Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya, 2004, 10th International Symposium on Software Metrics, 2004. Proceedings..

An application of zero-inflated Poisson regression for software fault prediction

Taghi M. Khoshgoftaar, K. Gao, R. M. Szabo, 2001, Proceedings 12th International Symposium on Software Reliability Engineering.

THREE-GROUP SOFTWARE QUALITY CLASSIFICATION MODELING USING AN AUTOMATED REASONING APPROACH

Taghi M. Khoshgoftaar, Naeem Seliya, 2004 .

Which Users Reply to and Interact with Twitter Social Bots?

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

From Web Service Artifact to a Readable and Verifiable Model

Taghi M. Khoshgoftaar, John C. Sloan, 2009, IEEE Transactions on Services Computing.

A Practical Software Quality Classification Model Using Genetic Programming

Taghi M. Khoshgoftaar, Yi Liu, 2007 .

Using Neural Networks to Predict Software Faults During

Taghi M. Khoshgoftaar, Robert M. Szabo, R. M. Szabo, 1996 .

Analyzing software quality with limited fault-proneness defect data

Taghi M. Khoshgoftaar, Naeem Seliya, Shi Zhong, 2005, Ninth IEEE International Symposium on High-Assurance Systems Engineering (HASE'05).

Analogy-Based Practical Classification Rules for Software Quality Estimation

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2003, Empirical Software Engineering.

Process measures for predicting software quality

Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, 1997, Proceedings 1997 High-Assurance Engineering Workshop.

The impact of software evolution and reuse on software quality

Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, 2004, Empirical Software Engineering.

Exploring Ensemble Filters for Software Defect Prediction

Taghi M. Khoshgoftaar, T. Khoshgoftaar, 2013 .

Assessment of a Multi-Strategy Classifier for an Embedded Software System

Taghi M. Khoshgoftaar, Kehan Gao, T. Khoshgoftaar, 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).

Predicting high-risk program modules by selecting the right software measurements

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2011, Software Quality Journal.

Improving neural network models of defect content in complex software systems

Taghi M. Khoshgoftaar, David L. Lanning, Peter Guasti, 1996, Defense + Commercial Sensing.

A study on rare fraud predictions with big Medicare claims fraud data

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2020, Intell. Data Anal..

An Empirical Study of the Noise Impact on Cost-Sensitive Learning

Xindong Wu, Taghi M. Khoshgoftaar, Yong Shi, 2007, IJCAI.

VipBoost: A More Accurate Boosting Algorithm

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2009, FLAIRS Conference.

Exploring Software Quality Classification with a Wrapper-Based Feature Ranking Technique

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2009, 2009 21st IEEE International Conference on Tools with Artificial Intelligence.

Identifying learners robust to low quality data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2008, 2008 IEEE International Conference on Information Reuse and Integration.

Efficient learning from big data for cancer risk modeling: A case study with melanoma

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2019, Comput. Biol. Medicine.

THE USE OF UNDER- AND OVERSAMPLING WITHIN ENSEMBLE FEATURE SELECTION AND CLASSIFICATION FOR SOFTWARE QUALITY PREDICTION

Taghi M. Khoshgoftaar, Kehan Gao, Randall Wald, 2014 .

Ensemble Coordination for Discrete Event Control

Taghi M. Khoshgoftaar, John C. Sloan, 2011, 2011 IEEE 13th International Symposium on High-Assurance Systems Engineering.

Feature Selection for Vibration Sensor Data Transformed by a Streaming Wavelet Packet Decomposition

Taghi M. Khoshgoftaar, Randall Wald, John C. Sloan, 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

Improving Software Quality Estimation by Combining Boosting and Feature Selection

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2013, 2013 12th International Conference on Machine Learning and Applications.

Impact of Noise and Data Sampling on Stability of Feature Selection

Taghi M. Khoshgoftaar, Randall Wald, Ahmad Abu Shanab, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Performance of Filter-based Feature Subset Selection for Software Quality Data Classification

Taghi M. Khoshgoftaar, 2014 .

Resampling or Reweighting: A Comparison of Boosting Implementations

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

The Impact of Malicious Accounts on Political Tweet Sentiment

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2018, 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC).

Medicare Fraud Detection Using Random Forest with Class Imbalanced Big Data

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

Using Twitter Content to Predict Psychopathy

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 11th International Conference on Machine Learning and Applications.

Detecting Network Attacks Based on Behavioral Commonalities

Taghi M. Khoshgoftaar, Amri Napolitano, Maryam M. Najafabadi, 2016 .

An empirical comparison of repetitive undersampling techniques

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2009, 2009 IEEE International Conference on Information Reuse & Integration.

The improved grey model based on particle swarm optimization algorithm for time series prediction

Taghi M. Khoshgoftaar, Lu Liu, Kewen Li, 2016, Eng. Appl. Artif. Intell..

Classification Performance of Rank Aggregation Techniques for Ensemble Gene Selection

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, FLAIRS Conference.

Software quality estimation with limited fault data: a semi-supervised learning perspective

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2007, Software Quality Journal.

Using Weather and Playing Surface to Predict the Occurrence of Injury in Major League Soccer Games: A Case Study

Taghi M. Khoshgoftaar, Michael F. Bergeron, Sara Landset, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

Prediction of software faults using fuzzy nonlinear regression modeling

Taghi M. Khoshgoftaar, Zhiwei Xu, Edward B. Allen, 2000, Proceedings. Fifth IEEE International Symposium on High Assurance Systems Engineering (HASE 2000).

Using Feature Selection to Determine Optimal Depth for Wavelet Packet Decomposition of Vibration Signals for Ocean System Reliability

Taghi M. Khoshgoftaar, Randall Wald, John C. Sloan, 2011, 2011 IEEE 13th International Symposium on High-Assurance Systems Engineering.

Predicting susceptibility to social bots on Twitter

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

A Comparative Study of Different Strategies for Predicting Software Quality

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2011, SEKE.

Ensemble vs. Data Sampling: Which Option Is Best Suited to Improve Classification Performance of Imbalanced Bioinformatics Data?

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI).

Enhancing software quality estimation using ensemble-classifier based noise filtering

Taghi M. Khoshgoftaar, Shi Zhong, V. H. Joshi, 2005, Intell. Data Anal..

Knowledge discovery from imbalanced and noisy data

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2009, Data Knowl. Eng..

Hybrid sampling for imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2009, Integr. Comput. Aided Eng..

An Empirical Study of the Classification Performance of Learners on Imbalanced and Noisy Software Quality Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, 2007 IEEE International Conference on Information Reuse and Integration.

ATTRIBUTE SELECTION USING ROUGH SETS IN SOFTWARE QUALITY CLASSIFICATION

Taghi M. Khoshgoftaar, Kehan Gao, Lofton A. Bullard, 2009 .

Using the genetic algorithm to build optimal neural networks for fault-prone module detection

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1996, Proceedings of ISSRE '96: 7th International Symposium on Software Reliability Engineering.

Application of a usage profile in software quality models

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999, Proceedings of the Third European Conference on Software Maintenance and Reengineering (Cat. No. PR00090).

Data quality in data mining and machine learning

Taghi M. Khoshgoftaar, Jason Van Hulse, 2007 .

An Empirical Study of Learning from Imbalanced Data Using Random Forest

Taghi M. Khoshgoftaar, Jason Van Hulse, Moiz Golawala, 2007, 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007).

The pairwise attribute noise detection algorithm

Taghi M. Khoshgoftaar, Jason Van Hulse, Haiying Huang, 2007, Knowledge and Information Systems.

Collaborative Filtering for Multi-class Data Using Belief Nets Algorithms

Taghi M. Khoshgoftaar, Xiaoyuan Su, T. Khoshgoftaar, 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).

A novel dataset-similarity-aware approach for evaluating stability of software metric selection techniques

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

An empirical study of predicting software faults with case-based reasoning

Taghi M. Khoshgoftaar, Naeem Seliya, Nandini Sundaresh, 2006, Software Quality Journal.

Resource-sensitive intrusion detection models for network traffic

Taghi M. Khoshgoftaar, M. E. Abushadi, 2004, Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings..

Uncertain Classification of Fault-Prone Software Modules

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 2002, Empirical Software Engineering.

A comparative study of filter-based feature ranking techniques

Taghi M. Khoshgoftaar, Kehan Gao, Huanjing Wang, 2010, 2010 IEEE International Conference on Information Reuse & Integration.

Classification tree models of software quality over multiple releases

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1999, Proceedings 10th International Symposium on Software Reliability Engineering (Cat. No.PR00443).

Application of Fuzzy Rule Extraction to Minimize the Costs of Misclassification on Software Quality Modeling

Taghi M. Khoshgoftaar, Zhiwei Xu, T. Khoshgoftaar, 2003 .

Indirect classification approaches: a comparative study in network intrusion detection

Taghi M. Khoshgoftaar, Hua Lin, Kehan Gao, 2006, Int. J. Comput. Appl. Technol..

Survey on categorical data for neural networks

Taghi M. Khoshgoftaar, John T. Hancock, John T. Hancock, 2020, Journal of Big Data.

Building and Interpreting Risk Models from Imbalanced Clinical Data

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2018, 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI).

A Survey of 2D Face Databases

Taghi M. Khoshgoftaar, Gabriel Castaneda Oscos, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

Measuring stability of feature ranking techniques: a noise-based approach

Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano, 2012, Int. J. Bus. Intell. Data Min..

Large-scale distributed L-BFGS

Taghi M. Khoshgoftaar, Maryam M. Najafabadi, Flavio Villanustre, 2017, Journal of Big Data.

Efficient Modeling of User-Entity Preference in Big Social Networks

Taghi M. Khoshgoftaar, Aaron N. Richter, Brian Heredia, 2015, 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI).

BASELINE-DIFFERENCING: A NOVEL APPROACH FOR BUILDING GENERALIZABLE OCEAN TURBINE RELIABILITY MODELS

Taghi M. Khoshgoftaar, Bassem Alhalabi, Randall Wald, 2012 .

Identifying Medicare Provider Fraud with Unsupervised Machine Learning

Taghi M. Khoshgoftaar, Richard A. Bauder, Raquel da Rosa, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

Medicare Fraud Detection Using Machine Learning Methods

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

An Empirical Study on Wrapper-Based Feature Selection for Software Engineering Data

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2013, 2013 12th International Conference on Machine Learning and Applications.

Feature Selection with Imbalanced Data for Software Defect Prediction

Taghi M. Khoshgoftaar, Kehan Gao, T. Khoshgoftaar, 2009, 2009 International Conference on Machine Learning and Applications.

Ontology-Based Business Process Customization for Composite Web Services

Xindong Wu, Taghi M. Khoshgoftaar, E. K. Park, 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

An Extendible Translation of BPEL to a Machine-verifiable Model

Taghi M. Khoshgoftaar, John C. Sloan, Augusto Varas, 2009, SEKE.

The dimensionality of program complexity

Taghi M. Khoshgoftaar, John C. Munson, 1989, ICSE '89.

Impact of class distribution on the detection of slow HTTP DoS attacks using Big Data

Taghi M. Khoshgoftaar, Chad L. Calvert, T. Khoshgoftaar, 2019, Journal of Big Data.

A comprehensive empirical evaluation of missing value imputation in noisy software measurement data

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2008, J. Syst. Softw..

Detection of fault-prone software modules during a spiral life cycle

Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, 1996, 1996 Proceedings of International Conference on Software Maintenance.

Learning with limited minority class data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

The necessity of assuring quality in software measurement data

Taghi M. Khoshgoftaar, Naeem Seliya, 2004 .

Filter-Based Subset Selection for Easy, Moderate, and Hard Bioinformatics Data

Taghi M. Khoshgoftaar, Ahmad Abu Shanab, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

Identification of microRNA biomarkers for cancer by combining multiple feature selection techniques

Abhijit S. Pandya, Taghi M. Khoshgoftaar, Hanqi Zhuang, 2011, J. Comput. Methods Sci. Eng..

An empirical investigation of filter attribute selection techniques for software quality classification

Taghi M. Khoshgoftaar, Kehan Gao, Huanjing Wang, 2009, 2009 IEEE International Conference on Information Reuse & Integration.

Measuring coupling and cohesion of software modules: an information-theory approach

Taghi M. Khoshgoftaar, Edward B. Allen, Ye Chen, 2001, Proceedings Seventh International Software Metrics Symposium.

Improving detection of untrustworthy online reviews using ensemble learners combined with feature selection

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2017, Social Network Analysis and Mining.

Software quality estimation with case-based reasoning

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2004, Adv. Comput..

An exploration of learning when data is noisy and imbalanced

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2011, Intell. Data Anal..

Applying Feature Selection to Short Time Wavelet Transformed Vibration Data for Reliability Analysis of an Ocean Turbine

Taghi M. Khoshgoftaar, Randall Wald, Janell Duhaney, 2012, 2012 11th International Conference on Machine Learning and Applications.

Predicting Cancer Relapse with Clinical Data: A Survey of Current Techniques

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2016, 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI).

The lines of code metric as a predictor of program faults: a critical analysis

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1990, Proceedings., Fourteenth Annual International Computer Software and Applications Conference.

Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures

Taghi M. Khoshgoftaar, Joseph D. Prusa, Ryan Sagul, 2019, Inf. Syst. Frontiers.

A survey on addressing high-class imbalance in big data

Taghi M. Khoshgoftaar, Naeem Seliya, Richard A. Bauder, 2018, Journal of Big Data.

An Investigation of Ensemble Techniques for Detection of Spam Reviews

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

Performance analysis of a peer-to-peer I/O architecture in video server environments

Taghi M. Khoshgoftaar, Khoa D. Huynh, 2005, Multimedia Tools and Applications.

Comparative aspects of software complexity metrics and program modules — a multidimensional scaling approach

Taghi M. Khoshgoftaar, John C. Munson, S. Ravichandran, 2005, Software Quality Journal.

A Novel Noise Filtering Algorithm for Imbalanced Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Genetic programming-based decision trees for software quality classification

Taghi M. Khoshgoftaar, Naeem Seliya, Yi Liu, 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

A COMPARATIVE STUDY OF FILTER-BASED AND WRAPPER-BASED FEATURE RANKING TECHNIQUES FOR SOFTWARE QUALITY MODELING

Taghi M. Khoshgoftaar, Kehan Gao, Lofton A. Bullard, 2011 .

An empirical study of the impact of count models predictions on module-order models

Taghi M. Khoshgoftaar, Kehan Gao, Erik Geleyn, 2002, Proceedings Eighth IEEE Symposium on Software Metrics.

Feature Level Sensor Fusion for Improved Fault Detection in MCM Systems for Ocean Turbines

Taghi M. Khoshgoftaar, Janell Duhaney, John C. Sloan, 2011, FLAIRS.

A Hybrid Approach to Coping with High Dimensionality and Class Imbalance for Software Defect Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2012, 2012 11th International Conference on Machine Learning and Applications.

Detection of SSH Brute Force Attacks Using Aggregated Netflow Data

Taghi M. Khoshgoftaar, Chad Calvert, Clifford Kemp, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Metric Selection for Software Defect Prediction

Taghi M. Khoshgoftaar, Jason Van Hulse, Kehan Gao, 2011, Int. J. Softw. Eng. Knowl. Eng..

The impact of costs of misclassification on software quality modeling

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1997, Proceedings Fourth International Software Metrics Symposium.

An Empirical Investigation on Wrapper-Based Feature Selection for Predicting Software Quality

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2015, Int. J. Softw. Eng. Knowl. Eng..

Predicting the order of fault-prone modules in legacy software

Taghi M. Khoshgoftaar, Edward B. Allen, 1998, Proceedings Ninth International Symposium on Software Reliability Engineering (Cat. No.98TB100257).

Software metrics and the quality of telecommunication software

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1992 .

Multivariate assessment of complex software systems: a comparative study

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1995, Proceedings of First IEEE International Conference on Engineering of Complex Computer Systems. ICECCS'95.

Training Convolutional Networks on Truncated Text

Taghi M. Khoshgoftaar, Joseph D. Prusa, 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

Application of neural networks to software quality modeling of a very large telecommunications system

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1997, IEEE Trans. Neural Networks.

Predicting Medical Provider Specialties to Detect Anomalous Insurance Claims

Taghi M. Khoshgoftaar, Aaron N. Richter, Richard A. Bauder, 2016, 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI).

Integrating Multiple Data Sources to Enhance Sentiment Prediction

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2016, 2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC).

Applications of information theory to software engineering measurement

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1994, Software Quality Journal.

An Empirical Study of Learning from Imbalanced Data Using Random Forest

Taghi M. Khoshgoftaar, J. Van Hulse, M. Golawala, 2007 .

Combining Feature Subset Selection and Data Sampling for Coping with Highly Imbalanced Software Data

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2015, SEKE.

Survey on RNN and CRF models for de-identification of medical free text

Taghi M. Khoshgoftaar, Flavio Villanustre, Joffrey L. Leevy, 2020, J. Big Data.

A Comparative Study of Threshold-Based Feature Selection Techniques

Taghi M. Khoshgoftaar, Jason Van Hulse, Huanjing Wang, 2010, 2010 IEEE International Conference on Granular Computing.

Applications of a relative complexity metric for software project management

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1990, J. Syst. Softw..

Application of fuzzy expert system in test case selection for system regression test

Taghi M. Khoshgoftaar, Zhiwei Xu, Kehan Gao, 2005, IRI -2005 IEEE International Conference on Information Reuse and Integration, Conf, 2005..

Are the principal components of software complexity data stable across software products?

Taghi M. Khoshgoftaar, David L. Lanning, T. Khoshgoftaar, 1994, Proceedings of 1994 IEEE 2nd International Software Metrics Symposium.

Software quality modeling: The impact of class noise on the random forest classifier

Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

A multiobjective module-order model for software quality enhancement

Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya, 2004, IEEE Transactions on Evolutionary Computation.

On the Rarity of Fault-prone Modules in Knowledge-based Software Quality Modeling

Taghi M. Khoshgoftaar, Naeem Seliya, D. J. Drown, 2008, SEKE.

Impact of noise and data sampling on stability of feature ranking techniques for biological datasets

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

Detecting Outliers Using Rule-Based Modeling for Improving CBR-Based Software Quality Classification Models

Taghi M. Khoshgoftaar, Kehan Gao, Lofton A. Bullard, 2003, ICCBR.

Count Models for Software Quality Estimation

Taghi M. Khoshgoftaar, Kehan Gao, T. Khoshgoftaar, 2007, IEEE Transactions on Reliability.

Melanoma risk modeling from limited positive samples

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2019, Network Modeling Analysis in Health Informatics and Bioinformatics.

Classification-tree models of software-quality over multiple releases

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 2000, IEEE Trans. Reliab..

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

Active learning with neural networks for intrusion detection

Taghi M. Khoshgoftaar, Naeem Seliya, 2010, 2010 IEEE International Conference on Information Reuse & Integration.

DYNAMIC MODELS FOR TESTING BASED ON TIME SERIES ANALYSIS

Taghi M. Khoshgoftaar, Robert M. Szabo, 2006 .

Using Genetic Programming to Determine Software Quality

Taghi M. Khoshgoftaar, Edward B. Allen, Matthew P. Evett, 1999, FLAIRS.

Evaluation of Wrapper-Based Feature Selection Using Hard, Moderate, and Easy Bioinformatics Data

Taghi M. Khoshgoftaar, Randall Wald, Ahmad Abu Shanab, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

Deep Learning and Data Sampling with Imbalanced Big Data

Taghi M. Khoshgoftaar, Justin M. Johnson, Justin M. Johnson, 2019, 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI).

An Empirical Study on Class Rarity in Big Data

Taghi M. Khoshgoftaar, Richard A. Bauder, Tawfiq Hasanin, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Rule-based noise detection for software measurement data

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2004, Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004..

Modernizing Analytics for Melanoma with a Large-Scale Research Dataset

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

Empirical Case Studies in Attribute Noise Detection

Taghi M. Khoshgoftaar, Jason Van Hulse, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

A Comparative Study of Ensemble Feature Selection Techniques for Software Defect Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Evaluation of Transfer Learning Algorithms Using Different Base Learners

Taghi M. Khoshgoftaar, Karl R. Weiss, T. Khoshgoftaar, 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

On the Stability of Feature Selection Methods in Software Quality Prediction: An Empirical Investigation

Taghi M. Khoshgoftaar, Naeem Seliya, Huanjing Wang, 2015, Int. J. Softw. Eng. Knowl. Eng..

An Evaluation of Sampling on Filter-Based Feature Selection Methods

Taghi M. Khoshgoftaar, Jason Van Hulse, Kehan Gao, 2010, FLAIRS Conference.

Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

A Hybrid Approach to Cleansing Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).

Case-Based Software Quality Prediction

Taghi M. Khoshgoftaar, K. Ganesan, Edward B. Allen, 2000, International journal of software engineering and knowledge engineering.

An Empirical Study of Software Metrics Selection Using Support Vector Machine

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2011, SEKE.

Accuracy of software quality models over multiple releases

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 2000, Ann. Softw. Eng..

A review of data mining using big data in health informatics

Taghi M. Khoshgoftaar, Randall Wald, Matthew Herland, 2013, Journal Of Big Data.

Software quality analysis by combining multiple projects and learners

Taghi M. Khoshgoftaar, Naeem Seliya, Pierre Rebours, 2008, Software Quality Journal.

The importance of performance metrics within wrapper feature selection

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

A Multi-Objective Software Quality Classification Model Using Genetic Programming

Taghi M. Khoshgoftaar, Yi Liu, T. Khoshgoftaar, 2007, IEEE Transactions on Reliability.

Predicting Faults in High Assurance Software

Taghi M. Khoshgoftaar, Jason Van Hulse, Naeem Seliya, 2010, 2010 IEEE 12th International Symposium on High Assurance Systems Engineering.

How the Choice of Wrapper Learner and Performance Metric Affects Subset Evaluation

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

TESTING AND FORMAL VERIFICATION OF SERVICE ORIENTED ARCHITECTURES

Taghi M. Khoshgoftaar, John C. Sloan, 2009 .

Alternative approaches for the use of metrics to order programs by complexity

Taghi M. Khoshgoftaar, John C. Munson, David L. Lanning, 1994, J. Syst. Softw..

Utilizing Netflow Data to Detect Slow Read Attacks

Taghi M. Khoshgoftaar, Chad Calvert, Clifford Kemp, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

Identifying modules which do not propagate errors

Taghi M. Khoshgoftaar, Edward B. Allen, J. M. Voas, 1999, Proceedings 1999 IEEE Symposium on Application-Specific Systems and Software Engineering and Technology. ASSET'99 (Cat. No.PR00122).

Resource oriented selection of rule-based classification models: An empirical case study

Taghi M. Khoshgoftaar, Naeem Seliya, Angela Herzberg, 2006, Software Quality Journal.

Investigating the relationship between time and predictive model maintenance

Taghi M. Khoshgoftaar, Naeem Seliya, Joffrey L. Leevy, 2020, Journal of Big Data.

Contrasting Undersampled Boosting with Internal and External Feature Selection for Patient Response Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 12th International Conference on Machine Learning and Applications.

Alterations to the Bootstrapping Process within Random Forest: A Case Study on Imbalanced Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

Detecting Noisy Instances with the Ensemble Filter: a Study in Software Quality Estimation

Taghi M. Khoshgoftaar, Naeem Seliya, Vedang H. Joshi, 2006, Int. J. Softw. Eng. Knowl. Eng..

Comparing software fault predictions of pure and zero-inflated Poisson regression models

Taghi M. Khoshgoftaar, Kehan Gao, Robert M. Szabo, 2005, Int. J. Syst. Sci..

Toward Model Checking Web Services Over the Web

Taghi M. Khoshgoftaar, John C. Sloan, 2008, SEKE.

A Probabilistic Programming Approach for Outlier Detection in Healthcare Claims

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

Choosing the Best Classification Performance Metric for Wrapper-based Software Metric Selection for Defect Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2014, SEKE.

Comparing Transfer Learning and Traditional Learning Under Domain Class Imbalance

Taghi M. Khoshgoftaar, Karl R. Weiss, T. Khoshgoftaar, 2017, 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA).

Multivariate outlier detection in medicare claims payments applying probabilistic programming methods

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2017, Health Services and Outcomes Research Methodology.

Building a Novel GP-Based Software Quality Classifier Using Multiple Validation Datasets

Taghi M. Khoshgoftaar, Yi Liu, Jenq-Foung Yao, 2007, 2007 IEEE International Conference on Information Reuse and Integration.

Using evolutionary sampling to mine imbalanced data

Taghi M. Khoshgoftaar, Ramaswamy Narayanan, Dennis J. Drown, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

Sample size determination for biomedical big data with limited labels

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2020, Network Modeling Analysis in Health Informatics and Bioinformatics.

Melanoma Risk Prediction with Structured Electronic Health Records

Taghi M. Khoshgoftaar, Aaron N. Richter, T. Khoshgoftaar, 2018, BCB.

The necessity of assuring quality in software measurement data

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2004, 10th International Symposium on Software Metrics, 2004. Proceedings..

Simplifying the Utilization of Machine Learning Techniques for Bioinformatics

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 12th International Conference on Machine Learning and Applications.

Detecting noisy instances with the rule-based classification model

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2005, Intell. Data Anal..

Predicting Fault-Prone Modules in Embedded Systems Using Analogy-Based Classification Models

Taghi M. Khoshgoftaar, Bojan Cukic, Naeem Seliya, 2002, Int. J. Softw. Eng. Knowl. Eng..

Selecting the Appropriate Ensemble Learning Approach for Balanced Bioinformatics Data

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, FLAIRS.

Patient response datasets: Challenges and opportunities

Taghi M. Khoshgoftaar, Randall Wald, T. Khoshgoftaar, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

Robustness of Threshold-Based Feature Rankers with Data Sampling on Noisy and Imbalanced Data

Taghi M. Khoshgoftaar, Randall Wald, Ahmad Abu Shanab, 2012, FLAIRS.

Threshold-based feature selection techniques for high-dimensional bioinformatics data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2012, Network Modeling Analysis in Health Informatics and Bioinformatics.

Using Ensemble Learners to Improve Classifier Performance on Tweet Sentiment Data

Taghi M. Khoshgoftaar, Joseph D. Prusa, David J. Dittman, 2015, 2015 IEEE International Conference on Information Reuse and Integration.

CLASSIFYING SOFTWARE MODULES INTO THREE RISK GROUPS

Taghi M. Khoshgoftaar, Robert M. Szabo, 2004 .

Data Sampling Approaches with Severely Imbalanced Big Data for Medicare Fraud Detection

Taghi M. Khoshgoftaar, Richard A. Bauder, Tawfiq Hasanin, 2018, 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI).

A Study of Software Metric Selection Techniques: stability Analysis and Defect Prediction Model Performance

Taghi M. Khoshgoftaar, Huanjing Wang, Qianhui Althea Liang, 2013, Int. J. Artif. Intell. Tools.

Experimental Studies on the Impact of Data Sampling with Severely Imbalanced Big Data

Taghi M. Khoshgoftaar, Richard A. Bauder, Tawfiq Hasanin, 2020 .

Empirical Case Studies in Attribute Noise Detection

Taghi M. Khoshgoftaar, J. Van Hulse, 2009, IEEE Trans. Syst. Man Cybern. Part C.

Polishing Noise in Continuous Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, International Conference on Software Engineering and Knowledge Engineering.

Cross-Domain Sentiment Analysis: An Empirical Investigation

Taghi M. Khoshgoftaar, Joseph D. Prusa, Brian Heredia, 2016, 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI).

Cbr-based software quality models and quality of data

Taghi M. Khoshgoftaar, Yudong Xiao, 2005 .

Improving tree-based models of software quality with principal components analysis

Taghi M. Khoshgoftaar, Edward B. Allen, Ruqun Shan, 2000, Proceedings 11th International Symposium on Software Reliability Engineering. ISSRE 2000.

Multiple Imputation of Missing Values in Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco, 2007 .

Software Quality Prediction for High-Assurance Network Telecommunications Systems

Taghi M. Khoshgoftaar, Zhiwei Xu, T. Khoshgoftaar, 2001, Computer/law journal.

Investigating the Variation of Ensemble Size on Bagging-Based Classifier Performance in Imbalanced Bioinformatics Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2016, 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI).

Comparison of rank-based vs. score-based aggregation for ensemble gene selection

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

Application of neural networks for predicting program faults

Abhijit S. Pandya, Taghi M. Khoshgoftaar, David L. Lanning, 1995, Ann. Softw. Eng..

Guest Editor's Introduction: Software Metrics

Taghi M. Khoshgoftaar, Paul W. Oman, T. Khoshgoftaar, 1994 .

Hybrid sampling for imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 IEEE International Conference on Information Reuse and Integration.

Measuring Stability of Feature Selection Techniques on Real-World Software Datasets

Taghi M. Khoshgoftaar, Huanjing Wang, Randall Wald, 2013 .

Unsupervised learning for expert-based software quality estimation

Taghi M. Khoshgoftaar, Naeem Seliya, Shi Zhong, 2004, Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings..

Making an accurate classifier ensemble by voting on classifications from imputed learning sets

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2009, Int. J. Inf. Decis. Sci..

Detection of fault-prone program modules in a very large telecommunications system

Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, 1995, Proceedings of Sixth International Symposium on Software Reliability Engineering. ISSRE'95.

Building Useful Models from Imbalanced Data with Sampling and Boosting

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, FLAIRS.

Software Engineering with Computational Intelligence and Machine Learning A Novel Software Metric Selection Technique Using the Area Under ROC Curves

Taghi M. Khoshgoftaar, Kehan Gao, 2010, SEKE.

Using Imputation Techniques to Help Learn Accurate Classifiers

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

Improving deep neural network design with new text data representations

Taghi M. Khoshgoftaar, Joseph D. Prusa, T. Khoshgoftaar, 2017, Journal of Big Data.

A Review of Ensemble Classification for DNA Microarrays Data

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

Noise elimination with partitioning filter for software quality estimation

Taghi M. Khoshgoftaar, Pierre Rebours, 2006, Int. J. Comput. Appl. Technol..

High Consequence Systems and Semantic Computing

Taghi M. Khoshgoftaar, Raymond A. Paul, Bojan Cukic, 2013, Int. J. Semantic Comput..

Evaluating noise elimination techniques for software quality estimation

Taghi M. Khoshgoftaar, Pierre Rebours, T. Khoshgoftaar, 2005, Intell. Data Anal..

Using product, process, and execution metrics to predict fault-prone software modules with classification trees

Taghi M. Khoshgoftaar, Edward B. Allen, Ruqun Shan, 2000, Proceedings. Fifth IEEE International Symposium on High Assurance Systems Engineering (HASE 2000).

Maximizing Classification Performance for Patient Response Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

A survey of open source tools for machine learning with big data in the Hadoop ecosystem

Taghi M. Khoshgoftaar, Aaron N. Richter, Sara Landset, 2015, Journal of Big Data.

Stability of filter- and wrapper-based software metric selection techniques

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

Comparison of Two Frameworks for Measuring the Stability of Gene-Selection Techniques on Noisy Class-Imbalanced Data

Taghi M. Khoshgoftaar, Randall Wald, Ahmad Abu Shanab, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

Is Gene Selection Enough for Imbalanced Bioinformatics Data?

Taghi M. Khoshgoftaar, Ahmad Abu Shanab, 2018, 2018 IEEE International Conference on Information Reuse and Integration (IRI).

Evaluating Feature Selection Methods for Network Intrusion Detection with Kyoto Data

Taghi M. Khoshgoftaar, Naeem Seliya, Maryam M. Najafabadi, 2016 .

A noise-based stability evaluation of threshold-based feature selection techniques

Wilker Altidor, Taghi M. Khoshgoftaar, Amri Napolitano, 2011, 2011 IEEE International Conference on Information Reuse & Integration.

Stability of Filter- and Wrapper-Based Feature Subset Selection

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

A Review of Performance Evaluation on 2D Face Databases

Taghi M. Khoshgoftaar, Gabriel Castaneda Oscos, 2017, 2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService).

The partitioning- and rule-based filter for noise detection

Taghi M. Khoshgoftaar, Naeem Seliya, Yudong Xiao, 2005, IRI -2005 IEEE International Conference on Information Reuse and Integration, Conf, 2005..

A Mixture Imputation-Boosted Collaborative Filter

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2008, FLAIRS.

Using Correlation-Based Feature Selection for a Diverse Collection of Bioinformatics Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

An assessment of software quality in a C++ environment

Taghi M. Khoshgoftaar, Robert M. Szabo, R. M. Szabo, 1995, Proceedings of Sixth International Symposium on Software Reliability Engineering. ISSRE'95.

Software Metrics: Charting the Course - Guest Editors' Introduction

Taghi M. Khoshgoftaar, Paul W. Oman, T. Khoshgoftaar, 1994, Computer.

Imputation-boosted collaborative filtering using machine learning classifiers

Taghi M. Khoshgoftaar, Xiaoyuan Su, Russell Greiner, 2008, SAC '08.

Analysis and differentiation of software system environments

Taghi M. Khoshgoftaar, David L. Lanning, T. Khoshgoftaar, 1996, Software Quality Journal.

Collaborative Filtering for Multi-Class Data Using Bayesian Networks

Taghi M. Khoshgoftaar, Xiaoyuan Su, 2008, Int. J. Artif. Intell. Tools.

Evaluating the impact of data quality on sampling

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2010, IRI.

Analyzing software measurement data with clustering techniques

Taghi M. Khoshgoftaar, Naeem Seliya, Shi Zhong, 2004, IEEE Intelligent Systems.

Utilizing Ensemble, Data Sampling and Feature Selection Techniques for Improving Classification Performance on Tweet Sentiment Data

Taghi M. Khoshgoftaar, Amri Napolitano, Joseph D. Prusa, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Effects of the Use of Boosting on Classification Performance of Imbalanced Bioinformatics Datasets

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

An extensive comparison of feature ranking aggregation techniques in bioinformatics

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

Integrating metrics and models for software risk assessment

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1996, Proceedings of ISSRE '96: 7th International Symposium on Software Reliability Engineering.

Early Quality Prediction: A Case Study in Telecommunications

Taghi M. Khoshgoftaar, Edward B. Allen, Nishith Goel, 1996, IEEE Softw..

The Detection of Fault-Prone Programs

Taghi M. Khoshgoftaar, John C. Munson, T. Khoshgoftaar, 1992, IEEE Trans. Software Eng..

Comparing Approaches for Combining Data Sampling and Feature Selection to Address Key Data Quality Issues in Tweet Sentiment Analysis

Taghi M. Khoshgoftaar, Joseph D. Prusa, 2016, FLAIRS Conference.

Feature Selection with High-Dimensional Imbalanced Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2009, 2009 IEEE International Conference on Data Mining Workshops.

High-Dimensional Software Engineering Data and Feature Selection

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2009, 2009 21st IEEE International Conference on Tools with Artificial Intelligence.

Survey of Data Cleansing and Monitoring for Large-Scale Battery Backup Installations

Taghi M. Khoshgoftaar, Randall Wald, Liz Aranguren Pachano, 2013, 2013 12th International Conference on Machine Learning and Applications.

Early operational risk assessment of software using fuzzy expert systems

Taghi M. Khoshgoftaar, Zhiwei Xu, Edward B. Allen, 2002, Proceedings of the 5th Biannual World Automation Congress.

Predicting software errors, during development, using nonlinear regression models: a comparative study

Taghi M. Khoshgoftaar, B. B. Bhattacharyya, G. D. Richardson, 1992 .

The impact of software enhancement on software reliability

Taghi M. Khoshgoftaar, D. L. Lanning, T. Khoshgoftaar, 1995 .

An application of a rule-based model in software quality classification

Taghi M. Khoshgoftaar, Kehan Gao, Lofton A. Bullard, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

A comparative study of pattern recognition techniques for quality evaluation of telecommunications software

Abhijit S. Pandya, Taghi M. Khoshgoftaar, David L. Lanning, 1994, IEEE J. Sel. Areas Commun..

A performance analysis of personal computers in a video conferencing environment

Taghi M. Khoshgoftaar, Khoa D. Huynh, T. Khoshgoftaar, 1994, Multimedia Systems.

Labeling Network Event Records for Intrusion Detection in aWireless LAN

Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

Predicting fault-prone modules with case-based reasoning

Taghi M. Khoshgoftaar, K. Ganesan, Edward B. Allen, 1997, Proceedings The Eighth International Symposium on Software Reliability Engineering.

Network Traffic Prediction Models for Near- and Long-Term Predictions

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

Stability of Three Forms of Feature Selection Methods on Software Engineering Data

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2015, SEKE.

Analysis of Transfer Learning Performance Measures

Taghi M. Khoshgoftaar, Karl R. Weiss, T. Khoshgoftaar, 2017, 2017 IEEE International Conference on Information Reuse and Integration (IRI).

An Investigation of Transfer Learning and Traditional Machine Learning Algorithms

Taghi M. Khoshgoftaar, Karl R. Weiss, T. Khoshgoftaar, 2016, 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI).

Learning from Software Quality Data with Class Imbalance and Noise

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, SEKE.

WRAPPER-BASED FEATURE RANKING TECHNIQUES FOR DETERMINING RELEVANCE OF SOFTWARE ENGINEERING METRICS

Wilker Altidor, Taghi M. Khoshgoftaar, Kehan Gao, 2010 .

A tree-based classification model for analysis of a military software system

Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, 1996, HASE.

Software Quality Imputation in the Presence of Noisy Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco, 2006, 2006 IEEE International Conference on Information Reuse & Integration.

Does the Inclusion of Data Sampling Improve the Performance of Boosting Algorithms on Imbalanced Bioinformatics Data?

Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Experimental perspectives on learning from imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2007, ICML '07.

Genetic programming model for software quality classification

Taghi M. Khoshgoftaar, Yi Liu, T. Khoshgoftaar, 2001, Proceedings Sixth IEEE International Symposium on High Assurance Systems Engineering. Special Topic: Impact of Networking.

Using neural networks to predict software faults during testing

Taghi M. Khoshgoftaar, Robert M. Szabo, 1996, IEEE Trans. Reliab..

Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI - 2004, November 8-10, 2004, Las Vegas Hilton, Las Vegas, NV, USA

Taghi M. Khoshgoftaar, Mei-Ling Shyu, Du Zhang, 2004, IRI.

Determining noisy instances relative to attributes of interest

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2006, Intell. Data Anal..

Reducing Feature Set Explosion to Facilitate Real-World Review Spam Detection

Taghi M. Khoshgoftaar, Joseph D. Prusa, Michael Crawford, 2016, FLAIRS Conference.

A Study on First Order Statistics-Based Feature Selection Techniques on Software Metric Data

Taghi M. Khoshgoftaar, Amri Napolitano, Huanjing Wang, 2013, International Conference on Software Engineering and Knowledge Engineering.

Cost-Benefit Analysis of Software Quality Models

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 2004, Software Quality Journal.

Application of fuzzy expert systems in assessing operational risk of software

Taghi M. Khoshgoftaar, Zhiwei Xu, Edward B. Allen, 2003, Inf. Softw. Technol..

Using classification trees for software quality models: lessons learned

Taghi M. Khoshgoftaar, Edward B. Allen, Archana Naik, 1998, Proceedings Third IEEE International High-Assurance Systems Engineering Symposium (Cat. No.98EX231).

Software Defect Prediction for High-Dimensional and Class-Imbalanced Data

Taghi M. Khoshgoftaar, Kehan Gao, T. Khoshgoftaar, 2011, SEKE.

Necessity of Feature Selection when Augmenting Tweet Sentiment Feature Spaces with Emoticons

Taghi M. Khoshgoftaar, Amri Napolitano, Joseph D. Prusa, 2016, FLAIRS.

Comparison of approaches to alleviate problems with high-dimensional and class-imbalanced data

Taghi M. Khoshgoftaar, Jason Van Hulse, Randall Wald, 2011, 2011 IEEE International Conference on Information Reuse & Integration.

Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2007, 2007 IEEE International Conference on Information Reuse and Integration.

Mining Data from Multiple Software Development Projects

Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao, 2009, 2009 IEEE International Conference on Data Mining Workshops.

The application of fuzzy enhanced case-based reasoning for identifying fault-prone modules

Taghi M. Khoshgoftaar, Donald F. Schenker, 1998, Proceedings Third IEEE International High-Assurance Systems Engineering Symposium (Cat. No.98EX231).

Using feature selection and classification to build effective and efficient firewalls

Taghi M. Khoshgoftaar, Randall Wald, Flavio Villanustre, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

A Comparison of Software Fault Imputation Procedures

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2006, 2006 5th International Conference on Machine Learning and Applications (ICMLA'06).

Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study

Taghi M. Khoshgoftaar, Naeem Seliya, T. Khoshgoftaar, 2004, Empirical Software Engineering.

How ranker and learner choice affects classification performance on noisy bioinformatics data

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

Reducing overfitting in genetic programming models for software quality classification

Taghi M. Khoshgoftaar, Yi Liu, T. Khoshgoftaar, 2004, Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings..

Fault-tolerant software reliability modeling using Petri Nets

Taghi M. Khoshgoftaar, Eduardo B. Fernandez, Shao-Wei Leu, 1991 .

STRATEGY AND APPLICATION OF DATA-DRIVEN TESTING OF AN OCEAN TURBINE DRIVETRAIN

Taghi M. Khoshgoftaar, Bassem Alhalabi, John C. Sloan, 2011 .

2010 Ninth International Conference on Machine Learning and Applications ICMLA 2010 Table of Contents

Taghi M. Khoshgoftaar, Jason Van Hulse, George Kesidis, 2010 .

Building Decision Tree Software Quality Classification Models Using Genetic Programming

Taghi M. Khoshgoftaar, Yi Liu, T. Khoshgoftaar, 2003, GECCO.

A comparative evaluation of feature ranking methods for high dimensional bioinformatics data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2011, 2011 IEEE International Conference on Information Reuse & Integration.

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine.

Measuring Stability of Threshold-Based Feature Selection Techniques

Taghi M. Khoshgoftaar, Huanjing Wang, 2011, 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence.

Hitting the Moving Target: Trials and Tribulations of Modeling Quality in Evolving Software Systems

Taghi M. Khoshgoftaar, John C. Munson, George E. Stark, 1998, International Conference on Smart Multimedia.

Predicting testability of program modules using a neural network

Taghi M. Khoshgoftaar, Zhiwei Xu, Edward B. Allen, 2000, Proceedings 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology.

Empirical case studies of combining software quality classification models

Taghi M. Khoshgoftaar, Laurent A. Nguyen, Erik Geleyn, 2003, Third International Conference on Quality Software, 2003. Proceedings..

Ordering Fault-Prone Software Modules

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 2003, Software Quality Journal.

The multiple imputation quantitative noise corrector

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2007, Intell. Data Anal..

An Empirical Investigation of Combining Filter-Based Feature Subset Selection and Data Sampling for Software Defect Prediction

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2015 .

Machine Learning for Detecting Brute Force Attacks at the Network Level

Taghi M. Khoshgoftaar, Naeem Seliya, Maryam M. Najafabadi, 2014, 2014 IEEE International Conference on Bioinformatics and Bioengineering.

The Effect of Dataset Size on Training Tweet Sentiment Classifiers

Taghi M. Khoshgoftaar, Naeem Seliya, Joseph D. Prusa, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Verifying the Security Characteristics of a Secure Physical Access Control Protocol

Taghi M. Khoshgoftaar, Bassem Alhalabi, Lofton A. Bullard, 2016 .

Classification of Fault-Prone Software Modules: Prior Probabilities, Costs, and Model Evaluation

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 1998, Empirical Software Engineering.

Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano, 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

A Novel Method for Fraudulent Medicare Claims Detection from Expected Payment Deviations (Application Paper)

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2016, 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI).

Decision Level Fusion of Wavelet Features for Ocean Turbine State Detection

Taghi M. Khoshgoftaar, Janell Duhaney, T. Khoshgoftaar, 2012, 2012 11th International Conference on Machine Learning and Applications.

Software metric-based neural network classification models of a very large telecommunications system

Taghi M. Khoshgoftaar, Edward B. Allen, John P. Hudepohl, 1996, Defense + Commercial Sensing.

Fuzzy logic techniques for software reliability engineering

Taghi M. Khoshgoftaar, Zhiwei Xu, 2001 .

Ensemble Gene Selection Versus Single Gene Selection: Which Is Better?

Taghi M. Khoshgoftaar, Randall Wald, David J. Dittman, 2013, FLAIRS Conference.

A Comparative Study of Sampled Feature Ranker Ensembles for Software Quality Classification

Taghi M. Khoshgoftaar, T. Khoshgoftaar, 2012 .

Improving Learner Performance with Data Sampling and Boosting

Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

Controlling Overfitting in Classification-Tree Models of Software Quality

Taghi M. Khoshgoftaar, Edward B. Allen, T. Khoshgoftaar, 2001, Empirical Software Engineering.

Software Quality Modeling as a Reliability Tool

Taghi M. Khoshgoftaar, Naeem Seliya, 2008, Wiley Encyclopedia of Computer Science and Engineering.

An Information Theoretic Approach to Predicting Software Faults

Taghi M. Khoshgoftaar, Edward B. Allen, 1998 .

Intrusion detection in wireless networks using clustering techniques with expert analysis

Taghi M. Khoshgoftaar, Naeem Seliya, Shi Zhong, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

Survey of Clinical Data Mining Applications on Big Data in Health Informatics

Taghi M. Khoshgoftaar, Randall Wald, Matthew Herland, 2013, 2013 12th International Conference on Machine Learning and Applications.

CLUSTERING-BASED NETWORK INTRUSION DETECTION

Taghi M. Khoshgoftaar, Naeem Seliya, Shi Zhong, 2007 .

The Impact of Feature Selection Techniques on a Hybrid Boosting and Data Sampling Approach for Software Quality Estimation

Taghi M. Khoshgoftaar, 2014 .

Exploring an iterative feature selection technique for highly imbalanced data sets

Taghi M. Khoshgoftaar, Amri Napolitano, Kehan Gao, 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

Using regression trees to classify fault-prone software modules

Taghi M. Khoshgoftaar, Edward B. Allen, Jianyu Deng, 2002, IEEE Trans. Reliab..

Software Engineering with Computational Intelligence

Taghi M. Khoshgoftaar, T. Khoshgoftaar, 2003 .

System regression test planning with a fuzzy expert system

Taghi M. Khoshgoftaar, Zhiwei Xu, Naeem Seliya, 2014, Inf. Sci..

Random forest implementation and optimization for Big Data analytics on LexisNexis’s high performance computing cluster platform

Taghi M. Khoshgoftaar, Borko Furht, Flavio Villanustre, 2019, Journal of Big Data.

Intrusion detection and Big Heterogeneous Data: a Survey

Taghi M. Khoshgoftaar, Randall Wald, Richard Zuech, 2015, Journal of Big Data.

A Progressive Edge-Based Stereo Correspondence Method

Taghi M. Khoshgoftaar, Xiaoyuan Su, T. Khoshgoftaar, 2007, ISVC.

Multivariate Anomaly Detection in Medicare using Model Residuals and Probabilistic Programming

Taghi M. Khoshgoftaar, Richard A. Bauder, T. Khoshgoftaar, 2017, FLAIRS.

Measuring dynamic program complexity

Taghi M. Khoshgoftaar, John C. Munson, 1992, IEEE Software.

The effect of noise level and distribution on classification of easy gene microarray data

Taghi M. Khoshgoftaar, Randall Wald, Ahmad Abu Shanab, 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

A New Intrusion Detection Benchmarking System

Taghi M. Khoshgoftaar, Naeem Seliya, Maryam M. Najafabadi, 2015, FLAIRS Conference.

A survey of stability analysis of feature subset selection techniques

Taghi M. Khoshgoftaar, Huanjing Wang, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques

Taghi M. Khoshgoftaar, Jason Van Hulse, Randall Wald, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Software quality modeling and analysis with limited or without defect data

Taghi M. Khoshgoftaar, Naeem Seliya, 2005 .

Return on investment of software quality predictions

Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, 1998, Proceedings. 1998 IEEE Workshop on Application-Specific Software Engineering and Technology. ASSET-98 (Cat. No.98EX183).

Predictive Modeling Techniques of Software Quality from Software Measures

Taghi M. Khoshgoftaar, John C. Munson, Bibhuti B. Bhattacharya, 1992, IEEE Trans. Software Eng..

An Empirical Study on Estimating Motions in Video Stabilization

Taghi M. Khoshgoftaar, Qiming Luo, 2007, 2007 IEEE International Conference on Information Reuse and Integration.

Filter- and wrapper-based feature selection for predicting user interaction with Twitter bots

Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald, 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).

Modeling and tracking Covid-19 cases using Big Data analytics on HPCC system platform

Taghi M. Khoshgoftaar, Borko Furht, Lili Xu, 2021, Journal of Big Data.

Detecting SQL Injection Web Attacks Using Ensemble Learners and Data Sampling

Taghi M. Khoshgoftaar, Richard Zuech, John T. Hancock, 2021, 2021 IEEE International Conference on Cyber Security and Resilience (CSR).

A Review and Analysis of the Bot-IoT Dataset

Taghi M. Khoshgoftaar, Joffrey L. Leevy, Jared M. Peterson, 2021, 2021 IEEE International Conference on Service-Oriented System Engineering (SOSE).

A reconstruction error-based framework for label noise detection

Taghi M. Khoshgoftaar, Joffrey L. Leevy, Zahra Salekshahrezaee, 2021, J. Big Data.

A literature review on one-class classification and its potential applications in big data

Taghi M. Khoshgoftaar, Naeem Seliya, Azadeh Abdollah Zadeh, 2021, J. Big Data.

Impact of Hyperparameter Tuning in Classifying Highly Imbalanced Big Data

Taghi M. Khoshgoftaar, John T. Hancock, T. Khoshgoftaar, 2021, 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI).

Output Thresholding for Ensemble Learners and Imbalanced Big Data

Taghi M. Khoshgoftaar, Justin M. Johnson, T. Khoshgoftaar, 2021, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI).

Investigating the Generalization of Image Classifiers with Augmented Test Sets

Taghi M. Khoshgoftaar, Connor Shorten, 2021, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI).

Detecting Slow Application-Layer DoS Attacks With PCA

Taghi M. Khoshgoftaar, Chad Calvert, Clifford Kemp, 2021, 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI).

Detecting cybersecurity attacks across different network features and learners

Taghi M. Khoshgoftaar, Joffrey L. Leevy, Richard Zuech, 2021, Journal of Big Data.

Feature Extraction for Class Imbalance Using a Convolutional Autoencoder and Data Sampling

Taghi M. Khoshgoftaar, Joffrey L. Leevy, Zahra Salekshahrezaee, 2021, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI).

Detecting web attacks using random undersampling and ensemble learners

Taghi M. Khoshgoftaar, Richard Zuech, John Hancock, 2021, J. Big Data.

IoT information theft prediction using ensemble feature selection

Taghi M. Khoshgoftaar, Joffrey L. Leevy, John Hancock, 2022, Journal of Big Data.

Using Inductive Transfer Learning to Improve Hotel Review Spam Detection

Taghi M. Khoshgoftaar, Michael Crawford, 2021, 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI).

An Examination of Neural Networks on Cluster Computers

Taghi M. Khoshgoftaar, Robert K. L. Kennedy, 2021, 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService).

Gradient Boosted Decision Tree Algorithms for Medicare Fraud Detection

Taghi M. Khoshgoftaar, John T. Hancock, T. Khoshgoftaar, 2021, SN Computer Science.

Predicting Traffic Incidents in Road Networks Using Vehicle Detector Data

Taghi M. Khoshgoftaar, Evangelos I. Kaisar, Aline Anacleto, 2021, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC).

Mitigating Class Imbalance for IoT Network Intrusion Detection: A Survey

Taghi M. Khoshgoftaar, Joffrey L. Leevy, Jared M. Peterson, 2021, 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService).

Text Data Augmentation for Deep Learning

Taghi M. Khoshgoftaar, Borko Furht, Connor Shorten, 2021, Journal of Big Data.

Detecting Web Attacks in Severely Imbalanced Network Traffic Data

Taghi M. Khoshgoftaar, Richard Zuech, John T. Hancock, 2021, 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI).

The Effects of Class Label Noise on Highly-Imbalanced Big Data

Taghi M. Khoshgoftaar, Justin M. Johnson, Robert K. L. Kennedy, 2021, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI).

Leveraging LightGBM for Categorical Big Data

Taghi M. Khoshgoftaar, John T. Hancock, T. Khoshgoftaar, 2021, 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService).

Medical Provider Embeddings for Healthcare Fraud Detection

Taghi M. Khoshgoftaar, Justin M. Johnson, T. Khoshgoftaar, 2021, SN Computer Science.

Encoding Techniques for High-Cardinality Features and Ensemble Learners

Taghi M. Khoshgoftaar, Justin M. Johnson, T. Khoshgoftaar, 2021, 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI).

Feature Selection Algorithms for Mining High Dimensional DNA Microarray Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Randall Wald, 2011 .

Computational Intelligence in Empirical Software Engineering

Taghi M. Khoshgoftaar, Ali Idri, T. Khoshgoftaar, 2004 .

A Review of Prognostics and Health Monitoring Techniques for Autonomous Ocean Systems

Taghi M. Khoshgoftaar, Randall Wald, John C. Sloan, 2010 .

Applications of Data Fusion in Monitoring Inaccessible Ocean Machinery

Taghi M. Khoshgoftaar, Ionut Cardei, Bassem Alhalabi, 2010 .

Proceedings, 16th IEEE International Conference on Tools with Artificial Intelligence : ICTAI 2004 : 15-17 November 2004, Boca Raton, Florida

Taghi M. Khoshgoftaar, T. Khoshgoftaar, 2004 .

Boosted Noise Filters for Identifying Mislabeled Data

Taghi M. Khoshgoftaar, Shi Zhong, Wei Tang, 2005 .

Software reliability model selection

Taghi M. Khoshgoftaar, Timothy G. Woodcock, T. Khoshgoftaar, 1992 .

Stability and Classification Performance of Feature Selection Techniques

Taghi M. Khoshgoftaar, Qianhui Althea Liang, Huanjing Wang, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

Improved Fault-Prone Detection Analysis of Software Modules Using an Evolutionary Neural Network Approach

Taghi M. Khoshgoftaar, Edward B. Allen, John Hudepohl, 2003 .

Approximating general distributions by a uniform coxian distribution

Taghi M. Khoshgoftaar, Harry G. Perros, 1988 .