J. V. Hulse

发表

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).

Imputation techniques for multivariate missingness in software measurement data

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

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.

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 pairwise attribute noise detection algorithm

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

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.

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

T. Khoshgoftaar, J. V. Hulse, Amri Napolitano, 2012, Network Modeling Analysis in Health Informatics and Bioinformatics.

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 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).

Experimental perspectives on learning from imbalanced data

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

Feature Selection with High-Dimensional Imbalanced Data

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

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.

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.

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).

Polishing Noise in Continuous Software Measurement Data

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

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.

Software Fault Imputation in Noisy and Incomplete Measurement Data

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

Knowledge discovery from imbalanced and noisy data

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

An exploration of learning when data is noisy and imbalanced

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

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.

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).

The multiple imputation quantitative noise corrector

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

Noise Correction using Bayesian Multiple Imputation

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

Class noise detection using frequent itemsets

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

Determining noisy instances relative to attributes of interest

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

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).

Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm

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

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

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

An empirical comparison of repetitive undersampling techniques

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

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).

Empirical Case Studies in Attribute Noise Detection

T. Khoshgoftaar, J. V. Hulse, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

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.

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.

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).

An Empirical Evaluation of Repetitive Undersampling Techniques

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

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.

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.

Metric Selection for Software Defect Prediction

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

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.

Building Useful Models from Imbalanced Data with Sampling and Boosting

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

Ensemble Feature Ranking Methods for Data Intensive Computing Applications

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

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.

Hybrid sampling for imbalanced data

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

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.

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.

The pairwise attribute noise detection algorithm

T. Khoshgoftaar, J. V. Hulse, Haiying Huang, 2007, Knowledge and Information Systems.

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.

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).

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..