Jason Van Hulse

64 papers A* 1B 5C 8Misc 17Journal 24Unranked 9
YearRankTypeTitle / Venue / Authors
2021 J jnl
Deep Learning Chromatic and Clique Numbers of Graphs.
CoRR
Jason Van Hulse, Joshua S. Friedman
2014 J jnl
An empirical study of the classification performance of learners on imbalanced and noisy software quality data.
Inf. Sci.
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco
2014 J jnl
Incomplete-case nearest neighbor imputation in software measurement data.
Inf. Sci.
Jason Van Hulse, Taghi M. Khoshgoftaar
2012 — conf
A Novel Noise-Resistant Boosting Algorithm for Class-Skewed Data.
ICMLA (2)
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2012 J jnl
Evaluation of the importance of data pre-processing order when combining feature selection and data sampling.
Int. J. Bus. Intell. Data Min.
Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse
2012 J jnl
Threshold-based feature selection techniques for high-dimensional bioinformatics data.
Netw. Model. Anal. Health Informatics Bioinform.
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald
2011 Misc conf
A comparative evaluation of feature ranking methods for high dimensional bioinformatics data.
IRI
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2011 J jnl
An exploration of learning when data is noisy and imbalanced.
Intell. Data Anal.
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2011 J jnl
Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data.
IEEE Trans. Syst. Man Cybern. Part A
Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2011 Misc conf
Comparison of approaches to alleviate problems with high-dimensional and class-imbalanced data.
IRI
Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse
2011 J jnl
Evaluating the Impact of Data Quality on Sampling.
J. Inf. Knowl. Manag.
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2011 J jnl
Metric Selection for Software Defect Prediction.
Int. J. Softw. Eng. Knowl. Eng.
Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse, Kehan Gao
2011 Misc conf
Robustness of Filter-Based Feature Ranking: A Case Study.
FLAIRS
Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse
2010 Misc conf
A Comparative Study of Threshold-Based Feature Selection Techniques.
GrC
Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
2010 C conf
A Novel Noise Filtering Algorithm for Imbalanced Data.
ICMLA
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2010 Misc conf
A novel feature selection technique for highly imbalanced data.
IRI
Taghi M. Khoshgoftaar, Kehan Gao, Jason Van Hulse
2010 J jnl
An Empirical Evaluation of Repetitive Undersampling Techniques.
Int. J. Softw. Eng. Knowl. Eng.
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2010 Misc conf
An Evaluation of Sampling on Filter-Based Feature Selection Methods.
FLAIRS
Kehan Gao, Taghi M. Khoshgoftaar, Jason Van Hulse
2010 C conf
Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques.
ICMLA
David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse
2010 Misc conf
Evaluating the impact of data quality on sampling.
IRI
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2010 — conf
Predicting Faults in High Assurance Software.
HASE
Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse
2010 J jnl
RUSBoost: A Hybrid Approach to Alleviating Class Imbalance.
IEEE Trans. Syst. Man Cybern. Part A
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2010 J jnl
Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors.
IEEE Trans. Neural Networks
Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2009 B conf
A Study on the Relationships of Classifier Performance Metrics.
ICTAI
Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse
2009 Misc conf
Aggregating Performance Metrics for Classifier Evaluation.
IRI
Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse
2009 Misc conf
An Empirical Comparison of Repetitive Undersampling Techniques.
IRI
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2009 B conf
An Empirical Study on Wrapper-Based Feature Ranking.
ICTAI
Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse
2009 J jnl
Empirical Case Studies in Attribute Noise Detection.
IEEE Trans. Syst. Man Cybern. Part C
Taghi M. Khoshgoftaar, Jason Van Hulse
2009 — conf
Feature Selection with High-Dimensional Imbalanced Data.
ICDM Workshops
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald
2009 J jnl
Hybrid sampling for imbalanced data.
Integr. Comput. Aided Eng.
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse
2009 J jnl
Identifying Learners Robust to Low Quality Data.
Informatica (Slovenia)
Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2009 J jnl
Improving Software-Quality Predictions With Data Sampling and Boosting.
IEEE Trans. Syst. Man Cybern. Part A
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse
2009 J jnl
Knowledge discovery from imbalanced and noisy data.
Data Knowl. Eng.
Jason Van Hulse, Taghi M. Khoshgoftaar
2008 — conf
A Comparative Study of Data Sampling and Cost Sensitive Learning.
ICDM Workshops
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008 J jnl
A comprehensive empirical evaluation of missing value imputation in noisy software measurement data.
J. Syst. Softw.
Jason Van Hulse, Taghi M. Khoshgoftaar
2008 Misc conf
Building Useful Models from Imbalanced Data with Sampling and Boosting.
FLAIRS
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008 Misc conf
Hybrid sampling for imbalanced data.
IRI
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse
2008 Misc conf
Identifying learners robust to low quality data.
IRI
Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Lofton A. Bullard
2008 — conf
Improving Learner Performance with Data Sampling and Boosting.
ICTAI (1)
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008 J jnl
Imputation techniques for multivariate missingness in software measurement data.
Softw. Qual. J.
Taghi M. Khoshgoftaar, Jason Van Hulse
2008 B conf
RUSBoost: Improving classification performance when training data is skewed.
ICPR
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008 — conf
Resampling or Reweighting: A Comparison of Boosting Implementations.
ICTAI (1)
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2008 B conf
Software quality modeling: The impact of class noise on the random forest classifier.
IEEE Congress on Evolutionary Computation
Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Lofton A. Bullard
2007 — conf
An Empirical Study of Learning from Imbalanced Data Using Random Forest.
ICTAI (2)
Taghi M. Khoshgoftaar, Moiz Golawala, Jason Van Hulse
2007 Misc conf
An Empirical Study of the Classification Performance of Learners on Imbalanced and Noisy Software Quality Data.
IRI
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco
2007 A* conf
Experimental perspectives on learning from imbalanced data.
ICML
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2007 Misc conf
Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data.
IRI
Jason Van Hulse, Taghi M. Khoshgoftaar
2007 C conf
Learning from Software Quality Data with Class Imbalance and Noise.
SEKE
Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert
2007 C conf
Learning with limited minority class data.
ICMLA
Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse, Amri Napolitano, Andres Folleco
2007 — conf
Mining Data with Rare Events: A Case Study.
ICTAI (2)
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano
2007 — conf
Skewed Class Distributions and Mislabeled Examples.
ICDM Workshops
Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
2007 J jnl
The multiple imputation quantitative noise corrector.
Intell. Data Anal.
Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, Lili Zhao
2007 J jnl
The pairwise attribute noise detection algorithm.
Knowl. Inf. Syst.
Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Huang
2006 C conf
A Comparison of Software Fault Imputation Procedures.
ICMLA
Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert
2006 B conf
A Hybrid Approach to Cleansing Software Measurement Data.
ICTAI
Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert
2006 J jnl
Class noise detection using frequent itemsets.
Intell. Data Anal.
Jason Van Hulse, Taghi M. Khoshgoftaar
2006 J jnl
Determining noisy instances relative to attributes of interest.
Intell. Data Anal.
Taghi M. Khoshgoftaar, Jason Van Hulse
2006 C conf
Multiple Imputation of Software Measurement Data: A Case Study.
SEKE
Taghi M. Khoshgoftaar, Jason Van Hulse
2006 Misc conf
Noise correction using bayesian multiple imputation.
IRI
Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert, Lili Zhao
2006 C conf
Polishing Noise in Continuous Software Measurement Data.
SEKE
Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse
2006 Misc conf
Software quality imputation in the presence of noisy data.
IRI
Taghi M. Khoshgoftaar, Andres Folleco, Jason Van Hulse, Lofton A. Bullard
2005 Misc conf
Empirical case studies in attribute noise detection.
IRI
Taghi M. Khoshgoftaar, Jason Van Hulse
2005 C conf
Identifying noise in an attribute of interest.
ICMLA
Taghi M. Khoshgoftaar, Jason Van Hulse
2005 J jnl
Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm.
Intell. Data Anal.
Taghi M. Khoshgoftaar, Jason Van Hulse