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Jason Van Hulse
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2020 – today
- 2021
- [i1]Jason Van Hulse, Joshua S. Friedman:
Deep Learning Chromatic and Clique Numbers of Graphs. CoRR abs/2108.01810 (2021)
2010 – 2019
- 2014
- [j23]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. Inf. Sci. 259: 571-595 (2014) - [j22]Jason Van Hulse, Taghi M. Khoshgoftaar:
Incomplete-case nearest neighbor imputation in software measurement data. Inf. Sci. 259: 596-610 (2014) - 2012
- [j21]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. Int. J. Bus. Intell. Data Min. 7(1/2): 116-134 (2012) - [j20]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano, Randall Wald:
Threshold-based feature selection techniques for high-dimensional bioinformatics data. Netw. Model. Anal. Health Informatics Bioinform. 1(1-2): 47-61 (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. Int. J. Softw. Eng. Knowl. Eng. 21(2): 237-257 (2011) - [j17]Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano:
Evaluating the Impact of Data Quality on Sampling. J. Inf. Knowl. Manag. 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 Trans. Syst. Man Cybern. 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 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. Int. J. Softw. Eng. Knowl. Eng. 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 Trans. 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 Trans. Syst. Man Cybern. 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 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. Integr. Comput. Aided Eng. 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 Trans. Syst. Man Cybern. 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 Trans. Syst. Man Cybern. 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. J. Syst. Softw. 81(5): 691-708 (2008) - [j6]Taghi M. Khoshgoftaar, Jason Van Hulse:
Imputation techniques for multivariate missingness in software measurement data. Softw. Qual. J. 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 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]Taghi M. Khoshgoftaar, Jason Van Hulse:
Identifying noise in an attribute of interest. ICMLA 2005 - [c1]Taghi M. Khoshgoftaar, Jason Van Hulse:
Empirical case studies in attribute noise detection. IRI 2005: 211-216
Coauthor Index
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