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Jason Van Hulse
2010 – today
- 2012
[j20]Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse: Evaluation of the importance of data pre-processing order when combining feature selection and data sampling. IJBIDM 7(1/2): 116-134 (2012)- [c40]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: A Novel Noise-Resistant Boosting Algorithm for Class-Skewed Data. ICMLA (2) 2012: 551-557
- 2011
- [j19]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: An exploration of learning when data is noisy and imbalanced. Intell. Data Anal. 15(2): 215-236 (2011)
- [j18]Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse, Kehan Gao: Metric Selection for Software Defect Prediction. International Journal of Software Engineering and Knowledge Engineering 21(2): 237-257 (2011)
- [j17]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: Evaluating the Impact of Data Quality on Sampling. JIKM 10(3): 225-245 (2011)
- [j16]Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data. IEEE Transactions on Systems, Man, and Cybernetics, Part A 41(3): 552-568 (2011)
- [c39]Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse: Robustness of Filter-Based Feature Ranking: A Case Study. FLAIRS Conference 2011
- [c38]Ahmad Abu Shanab, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse: Comparison of approaches to alleviate problems with high-dimensional and class-imbalanced data. IRI 2011: 234-239
- [c37]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: A comparative evaluation of feature ranking methods for high dimensional bioinformatics data. IRI 2011: 315-320
- 2010
- [j15]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: An Empirical Evaluation of Repetitive Undersampling Techniques. International Journal of Software Engineering and Knowledge Engineering 20(2): 173-195 (2010)
- [j14]Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors. IEEE Transactions on Neural Networks 21(5): 813-830 (2010)
- [j13]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: RUSBoost: A Hybrid Approach to Alleviating Class Imbalance. IEEE Transactions on Systems, Man, and Cybernetics, Part A 40(1): 185-197 (2010)
- [c36]Kehan Gao, Taghi M. Khoshgoftaar, Jason Van Hulse: An Evaluation of Sampling on Filter-Based Feature Selection Methods. FLAIRS Conference 2010
- [c35]Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse: A Comparative Study of Threshold-Based Feature Selection Techniques. GrC 2010: 499-504
- [c34]Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse: Predicting Faults in High Assurance Software. HASE 2010: 26-34
- [c33]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: A Novel Noise Filtering Algorithm for Imbalanced Data. ICMLA 2010: 9-14
- [c32]David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse: Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques. ICMLA 2010: 147-152
- [c31]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: Evaluating the impact of data quality on sampling. IRI 2010: 31-36
- [c30]Taghi M. Khoshgoftaar, Kehan Gao, Jason Van Hulse: A novel feature selection technique for highly imbalanced data. IRI 2010: 80-85
2000 – 2009
- 2009
- [j12]Jason Van Hulse, Taghi M. Khoshgoftaar: Knowledge discovery from imbalanced and noisy data. Data Knowl. Eng. 68(12): 1513-1542 (2009)
- [j11]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse: Hybrid sampling for imbalanced data. Integrated Computer-Aided Engineering 16(3): 193-210 (2009)
- [j10]Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Identifying Learners Robust to Low Quality Data. Informatica (Slovenia) 33(3): 245-259 (2009)
- [j9]Taghi M. Khoshgoftaar, Jason Van Hulse: Empirical Case Studies in Attribute Noise Detection. IEEE Transactions on Systems, Man, and Cybernetics, Part C 39(4): 379-388 (2009)
- [j8]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse: Improving Software-Quality Predictions With Data Sampling and Boosting. IEEE Transactions on Systems, Man, and Cybernetics, Part A 39(6): 1283-1294 (2009)
- [c29]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald: Feature Selection with High-Dimensional Imbalanced Data. ICDM Workshops 2009: 507-514
- [c28]Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse: A Study on the Relationships of Classifier Performance Metrics. ICTAI 2009: 59-66
- [c27]Wilker Altidor, Taghi M. Khoshgoftaar, Jason Van Hulse: An Empirical Study on Wrapper-Based Feature Ranking. ICTAI 2009: 75-82
- [c26]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: An Empirical Comparison of Repetitive Undersampling Techniques. IRI 2009: 29-34
- [c25]Naeem Seliya, Taghi M. Khoshgoftaar, Jason Van Hulse: Aggregating Performance Metrics for Classifier Evaluation. IRI 2009: 35-40
- 2008
- [j7]Jason Van Hulse, Taghi M. Khoshgoftaar: A comprehensive empirical evaluation of missing value imputation in noisy software measurement data. Journal of Systems and Software 81(5): 691-708 (2008)
- [j6]Taghi M. Khoshgoftaar, Jason Van Hulse: Imputation techniques for multivariate missingness in software measurement data. Software Quality Journal 16(4): 563-600 (2008)
- [c24]Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Lofton A. Bullard: Software quality modeling: The impact of class noise on the random forest classifier. IEEE Congress on Evolutionary Computation 2008: 3853-3859
- [c23]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Building Useful Models from Imbalanced Data with Sampling and Boosting. FLAIRS Conference 2008: 306-311
- [c22]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: A Comparative Study of Data Sampling and Cost Sensitive Learning. ICDM Workshops 2008: 46-52
- [c21]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: RUSBoost: Improving classification performance when training data is skewed. ICPR 2008: 1-4
- [c20]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Resampling or Reweighting: A Comparison of Boosting Implementations. ICTAI (1) 2008: 445-451
- [c19]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Improving Learner Performance with Data Sampling and Boosting. ICTAI (1) 2008: 452-459
- [c18]Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Lofton A. Bullard: Identifying learners robust to low quality data. IRI 2008: 190-195
- [c17]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse: Hybrid sampling for imbalanced data. IRI 2008: 202-207
- 2007
- [j5]Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, Lili Zhao: The multiple imputation quantitative noise corrector. Intell. Data Anal. 11(3): 245-263 (2007)
- [j4]Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Huang: The pairwise attribute noise detection algorithm. Knowl. Inf. Syst. 11(2): 171-190 (2007)
- [c16]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: Skewed Class Distributions and Mislabeled Examples. ICDM Workshops 2007: 477-482
- [c15]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano: Experimental perspectives on learning from imbalanced data. ICML 2007: 935-942
- [c14]Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse, Amri Napolitano, Andres Folleco: Learning with limited minority class data. ICMLA 2007: 348-353
- [c13]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Amri Napolitano: Mining Data with Rare Events: A Case Study. ICTAI (2) 2007: 132-139
- [c12]Taghi M. Khoshgoftaar, Moiz Golawala, Jason Van Hulse: An Empirical Study of Learning from Imbalanced Data Using Random Forest. ICTAI (2) 2007: 310-317
- [c11]Jason Van Hulse, Taghi M. Khoshgoftaar: Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data. IRI 2007: 630-637
- [c10]Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van Hulse, Andres Folleco: An Empirical Study of the Classification Performance of Learners on Imbalanced and Noisy Software Quality Data. IRI 2007: 651-658
- [c9]Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert: Learning from Software Quality Data with Class Imbalance and Noise. SEKE 2007: 487-
- 2006
- [j3]Taghi M. Khoshgoftaar, Jason Van Hulse: Determining noisy instances relative to attributes of interest. Intell. Data Anal. 10(3): 251-268 (2006)
- [j2]Jason Van Hulse, Taghi M. Khoshgoftaar: Class noise detection using frequent itemsets. Intell. Data Anal. 10(6): 487-507 (2006)
- [c8]Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert: A Comparison of Software Fault Imputation Procedures. ICMLA 2006: 135-142
- [c7]Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert: A Hybrid Approach to Cleansing Software Measurement Data. ICTAI 2006: 713-722
- [c6]Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert, Lili Zhao: Noise correction using bayesian multiple imputation. IRI 2006: 478-483
- [c5]Taghi M. Khoshgoftaar, Andres Folleco, Jason Van Hulse, Lofton A. Bullard: Software quality imputation in the presence of noisy data. IRI 2006: 484-489
- [c4]Taghi M. Khoshgoftaar, Jason Van Hulse: Multiple Imputation of Software Measurement Data: A Case Study. SEKE 2006: 220-226
- [c3]Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse: Polishing Noise in Continuous Software Measurement Data. SEKE 2006: 227-231
- 2005
- [j1]Taghi M. Khoshgoftaar, Jason Van Hulse: Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm. Intell. Data Anal. 9(6): 589-602 (2005)
- [c2]
- [c1]Taghi M. Khoshgoftaar, Jason Van Hulse: Empirical case studies in attribute noise detection. IRI 2005: 211-216
Coauthor Index
[j20] [c40] [j19] [j18] [j17] [j16] [c39] [c38] [c37] [j15] [j14] [j13] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [j12] [j11] [j10] [j9] [j8] [c29] [c28] [c27] [c26] [c25] [j7] [j6] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [j5] [j4] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [j3] [j2] [c8] [c7] [c6] [c5] [c4] [c3] [j1] [c2] [c1]
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last updated on 2013-06-11 10:01 CEST by the dblp team