Jason Van Hulse

发表

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.

Noise Correction using Bayesian Multiple Imputation

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

Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data

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

Ensemble Feature Ranking Methods for Data Intensive Computing Applications

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

Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm

Taghi M. Khoshgoftaar, Jason Van Hulse, T. Khoshgoftaar, 2005, 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).

Skewed Class Distributions and Mislabeled Examples

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

Aggregating performance metrics for classifier evaluation

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

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 .

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 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.

Imputation techniques for multivariate missingness in software measurement data

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

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.

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.

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 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.

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).

An Empirical Evaluation of Repetitive Undersampling Techniques

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

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.

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 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.

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..

Class noise detection using frequent itemsets

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

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..

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.

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.

An empirical comparison of repetitive undersampling techniques

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

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.

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.

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..

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 exploration of learning when data is noisy and imbalanced

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

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.

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.

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).

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.

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).

An Evaluation of Sampling on Filter-Based Feature Selection Methods

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

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).

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.

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.

Polishing Noise in Continuous Software Measurement Data

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

Multiple Imputation of Missing Values in Software Measurement Data

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

Hybrid sampling for imbalanced data

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

Building Useful Models from Imbalanced Data with Sampling and Boosting

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

Evaluating the impact of data quality on sampling

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

Feature Selection with High-Dimensional Imbalanced Data

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

Learning from Software Quality Data with Class Imbalance and Noise

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

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.

Experimental perspectives on learning from imbalanced data

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

Determining noisy instances relative to attributes of interest

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

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.

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).

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

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

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 multiple imputation quantitative noise corrector

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

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.

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.

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.

Deep Learning Chromatic and Clique Numbers of Graphs pdf

Jason Van Hulse, Joshua S. Friedman, 2021, ArXiv.

Feature Selection Algorithms for Mining High Dimensional DNA Microarray Data

Taghi M. Khoshgoftaar, Jason Van Hulse, Randall Wald, 2011 .