Jason Van Hulse

Joshua S. Friedman

CoRR, 2021

2014

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

[BibT_eX]

[DOI]

Inf. Sci., 2014

Incomplete-case nearest neighbor imputation in software measurement data.

[BibT_eX]

[DOI]

Inf. Sci., 2014

2012

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

[BibT_eX]

[DOI]

Netw. Model. Anal. Health Informatics Bioinform., 2012

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

[BibT_eX]

[DOI]

Ahmad Abu Shanab

Int. J. Bus. Intell. Data Min., 2012

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

[BibT_eX]

[DOI]

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2011

Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part A, 2011

Evaluating the Impact of Data Quality on Sampling.

[BibT_eX]

[DOI]

J. Inf. Knowl. Manag., 2011

Metric Selection for Software Defect Prediction.

[BibT_eX]

[DOI]

Huanjing Wang

Kehan Gao

Int. J. Softw. Eng. Knowl. Eng., 2011

An exploration of learning when data is noisy and imbalanced.

[BibT_eX]

[DOI]

Intell. Data Anal., 2011

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

[BibT_eX]

[DOI]

Ahmad Abu Shanab

Proceedings of the IEEE International Conference on Information Reuse and Integration, 2011

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

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Information Reuse and Integration, 2011

Robustness of Filter-Based Feature Ranking: A Case Study.

[BibT_eX]

[DOI]

Wilker Altidor

Proceedings of the Twenty-Fourth International Florida Artificial Intelligence Research Society Conference, 2011

2010

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part A, 2010

Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks, 2010

An Empirical Evaluation of Repetitive Undersampling Techniques.

[BibT_eX]

[DOI]

Int. J. Softw. Eng. Knowl. Eng., 2010

A novel feature selection technique for highly imbalanced data.

[BibT_eX]

[DOI]

Kehan Gao

Proceedings of the IEEE International Conference on Information Reuse and Integration, 2010

A Novel Noise Filtering Algorithm for Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

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

[BibT_eX]

[DOI]

David J. Dittman

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Predicting Faults in High Assurance Software.

[BibT_eX]

[DOI]

Naeem Seliya

Proceedings of the 12th IEEE High Assurance Systems Engineering Symposium, 2010

A Comparative Study of Threshold-Based Feature Selection Techniques.

[BibT_eX]

[DOI]

Huanjing Wang

Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010

An Evaluation of Sampling on Filter-Based Feature Selection Methods.

[BibT_eX]

[DOI]

Kehan Gao

Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009

Improving Software-Quality Predictions With Data Sampling and Boosting.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part A, 2009

Empirical Case Studies in Attribute Noise Detection.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part C, 2009

Identifying Learners Robust to Low Quality Data.

[BibT_eX]

[DOI]

Informatica (Slovenia), 2009

Hybrid sampling for imbalanced data.

[BibT_eX]

[DOI]

Integr. Comput. Aided Eng., 2009

Knowledge discovery from imbalanced and noisy data.

[BibT_eX]

[DOI]

Data Knowl. Eng., 2009

Aggregating Performance Metrics for Classifier Evaluation.

[BibT_eX]

[DOI]

Naeem Seliya

Proceedings of the IEEE International Conference on Information Reuse and Integration, 2009

An Empirical Comparison of Repetitive Undersampling Techniques.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Information Reuse and Integration, 2009

A Study on the Relationships of Classifier Performance Metrics.

[BibT_eX]

[DOI]

Naeem Seliya

Proceedings of the ICTAI 2009, 2009

An Empirical Study on Wrapper-Based Feature Ranking.

[BibT_eX]

[DOI]

Wilker Altidor

Proceedings of the ICTAI 2009, 2009

Feature Selection with High-Dimensional Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the ICDM Workshops 2009, 2009

2008

Imputation techniques for multivariate missingness in software measurement data.

[BibT_eX]

[DOI]

Softw. Qual. J., 2008

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

[BibT_eX]

[DOI]

J. Syst. Softw., 2008

Identifying learners robust to low quality data.

[BibT_eX]

[DOI]

Lofton A. Bullard

Proceedings of the IEEE International Conference on Information Reuse and Integration, 2008

Improving Learner Performance with Data Sampling and Boosting.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), 2008

Resampling or Reweighting: A Comparison of Boosting Implementations.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), 2008

RUSBoost: Improving classification performance when training data is skewed.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

A Comparative Study of Data Sampling and Cost Sensitive Learning.

[BibT_eX]

[DOI]

Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Building Useful Models from Imbalanced Data with Sampling and Boosting.

[BibT_eX]

[DOI]

Proceedings of the Twenty-First International Florida Artificial Intelligence Research Society Conference, 2008

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

[BibT_eX]

[DOI]

Lofton A. Bullard

Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007

The pairwise attribute noise detection algorithm.

[BibT_eX]

[DOI]

Haiying Huang

Knowl. Inf. Syst., 2007

The multiple imputation quantitative noise corrector.

[BibT_eX]

[DOI]

Lili Zhao

Intell. Data Anal., 2007

Learning from Software Quality Data with Class Imbalance and Noise.

[BibT_eX]

Proceedings of the Nineteenth International Conference on Software Engineering & Knowledge Engineering (SEKE'2007), 2007

Mining Data with Rare Events: A Case Study.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 2007

An Empirical Study of Learning from Imbalanced Data Using Random Forest.

[BibT_eX]

[DOI]

Moiz Golawala

Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 2007

Learning with limited minority class data.

[BibT_eX]

[DOI]

Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007

Experimental perspectives on learning from imbalanced data.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

Skewed Class Distributions and Mislabeled Examples.

[BibT_eX]

[DOI]

Proceedings of the Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006

Determining noisy instances relative to attributes of interest.

[BibT_eX]

[DOI]

Intell. Data Anal., 2006

Class noise detection using frequent itemsets.

[BibT_eX]

[DOI]

Intell. Data Anal., 2006

Polishing Noise in Continuous Software Measurement Data.

[BibT_eX]

Proceedings of the Eighteenth International Conference on Software Engineering & Knowledge Engineering (SEKE'2006), 2006

Multiple Imputation of Software Measurement Data: A Case Study.

[BibT_eX]

Proceedings of the Eighteenth International Conference on Software Engineering & Knowledge Engineering (SEKE'2006), 2006

Software quality imputation in the presence of noisy data.

[BibT_eX]

[DOI]

Lofton A. Bullard

Proceedings of the 2006 IEEE International Conference on Information Reuse and Integration, 2006

Noise correction using bayesian multiple imputation.

[BibT_eX]

[DOI]

Lili Zhao

Proceedings of the 2006 IEEE International Conference on Information Reuse and Integration, 2006

A Hybrid Approach to Cleansing Software Measurement Data.

[BibT_eX]

[DOI]

Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2006), 2006

A Comparison of Software Fault Imputation Procedures.

[BibT_eX]

[DOI]

Proceedings of the Fifth International Conference on Machine Learning and Applications, 2006

2005

Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm.

[BibT_eX]

[DOI]

Intell. Data Anal., 2005

Identifying noise in an attribute of interest.

[BibT_eX]

[DOI]