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Taghi M. Khoshgoftaar - Publications

Affiliations: 
Florida Atlantic University, Boca Raton, FL, United States 
Area:
Computer Science, Statistics
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253 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2023 Johnson JM, Khoshgoftaar TM. Data-Centric AI for Healthcare Fraud Detection. Sn Computer Science. 4: 389. PMID 37200563 DOI: 10.1007/s42979-023-01809-x  0.346
2020 Leevy JL, Khoshgoftaar TM, Villanustre F. Survey on RNN and CRF models for de-identification of medical free text Journal of Big Data. 7: 1-22. DOI: 10.1186/S40537-020-00351-4  0.369
2020 Hancock JT, Khoshgoftaar TM. Survey on categorical data for neural networks Journal of Big Data. 7. DOI: 10.1186/S40537-020-00305-W  0.354
2020 Hasanin T, Khoshgoftaar TM, Leevy JL, Bauder RA. Investigating class rarity in big data Journal of Big Data. 7. DOI: 10.1186/S40537-020-00301-0  0.401
2020 Johnson JM, Khoshgoftaar TM. The Effects of Data Sampling with Deep Learning and Highly Imbalanced Big Data Information Systems Frontiers. 1-19. DOI: 10.1007/S10796-020-10022-7  0.417
2019 Herrera VM, Khoshgoftaar TM, Villanustre F, Furht B. Random forest implementation and optimization for Big Data analytics on LexisNexis’s high performance computing cluster platform Journal of Big Data. 6. DOI: 10.1186/S40537-019-0232-1  0.372
2019 Calvert CL, Khoshgoftaar TM. Impact of class distribution on the detection of slow HTTP DoS attacks using Big Data Journal of Big Data. 6. DOI: 10.1186/S40537-019-0230-3  0.369
2019 Johnson JM, Khoshgoftaar TM. Medicare fraud detection using neural networks Journal of Big Data. 6. DOI: 10.1186/S40537-019-0225-0  0.421
2019 Johnson JM, Khoshgoftaar TM. Survey on deep learning with class imbalance Journal of Big Data. 6. DOI: 10.1186/S40537-019-0192-5  0.395
2019 Kennedy RKL, Khoshgoftaar TM, Villanustre F, Humphrey T. A parallel and distributed stochastic gradient descent implementation using commodity clusters Journal of Big Data. 6. DOI: 10.1186/S40537-019-0179-2  0.323
2018 Herland M, Bauder RA, Khoshgoftaar TM. Approaches for identifying U.S. medicare fraud in provider claims data. Health Care Management Science. PMID 30368641 DOI: 10.1007/S10729-018-9460-8  0.388
2018 Sohangir S, Wang D, Pomeranets A, Khoshgoftaar TM. Big Data: Deep Learning for financial sentiment analysis Journal of Big Data. 5. DOI: 10.1186/S40537-017-0111-6  0.356
2017 Najafabadi MM, Khoshgoftaar TM, Villanustre F, Holt J. Large-scale distributed L-BFGS Journal of Big Data. 4. DOI: 10.1186/S40537-017-0084-5  0.335
2016 Carryl C, Alhalabi B, Khoshgoftaar TM, Bullard L. Verifying the Security Characteristics of a Secure Physical Access Control Protocol International Journal of Reliability, Quality and Safety Engineering. 23. DOI: 10.1142/S0218539316500066  0.744
2016 Najafabadi MM, Khoshgoftaar TM, Napolitano A. Detecting Network Attacks Based on Behavioral Commonalities International Journal of Reliability, Quality and Safety Engineering. 23. DOI: 10.1142/S0218539316500054  0.534
2016 Najafabadi MM, Khoshgoftaar TM, Seliya N. Evaluating Feature Selection Methods for Network Intrusion Detection with Kyoto Data International Journal of Reliability, Quality and Safety Engineering. DOI: 10.1142/S0218539316500017  0.717
2016 Prusa J, Khoshgoftaar TM, Seliya N. The effect of dataset size on training tweet sentiment classifiers Proceedings - 2015 Ieee 14th International Conference On Machine Learning and Applications, Icmla 2015. 96-102. DOI: 10.1109/ICMLA.2015.22  0.664
2016 Bauder R, Khoshgoftaar TM, Seliya N. A survey on the state of healthcare upcoding fraud analysis and detection Health Services and Outcomes Research Methodology. 17: 31-55. DOI: 10.1007/S10742-016-0154-8  0.667
2015 Wang H, Khoshgoftaar TM, Napolitano A. Stability of three forms of feature selection methods on software engineering data Proceedings of the International Conference On Software Engineering and Knowledge Engineering, Seke. 2015: 385-390. DOI: 10.18293/SEKE2015!-198  0.568
2015 Zuech R, Khoshgoftaar TM, Wald R. Intrusion detection and Big Heterogeneous Data: a Survey Journal of Big Data. 2. DOI: 10.1186/S40537-015-0013-4  0.795
2015 Najafabadi MM, Villanustre F, Khoshgoftaar TM, Seliya N, Wald R, Muharemagic E. Deep learning applications and challenges in big data analytics Journal of Big Data. 2. DOI: 10.1186/S40537-014-0007-7  0.804
2015 Gao K, Khoshgoftaar TM, Napolitano A. An Empirical Investigation of Combining Filter-Based Feature Subset Selection and Data Sampling for Software Defect Prediction International Journal of Reliability, Quality and Safety Engineering. 22: 1550027. DOI: 10.1142/S0218539315500278  0.75
2015 Khoshgoftaar TM, Gao K, Chen Y, Napolitano A. Comparing Feature Selection Techniques for Software Quality Estimation Using Data-Sampling-Based Boosting Algorithms International Journal of Reliability, Quality and Safety Engineering. 22: 1550013. DOI: 10.1142/S0218539315500138  0.752
2015 Gao K, Khoshgoftaar TM. Assessments of feature selection techniques with respect to data sampling for highly imbalanced software measurement data International Journal of Reliability, Quality and Safety Engineering. 22. DOI: 10.1142/S0218539315500102  0.663
2015 Gao K, Khoshgoftaar TM, Napolitano A. Aggregating Data Sampling with Feature Subset Selection to Address Skewed Software Defect Data International Journal of Software Engineering and Knowledge Engineering. 25: 1531-1550. DOI: 10.1142/S0218194015400318  0.739
2015 Wang H, Khoshgoftaar TM, Seliya N. On the stability of feature selection methods in software quality prediction: An empirical investigation International Journal of Software Engineering and Knowledge Engineering. 25: 1467-1490. DOI: 10.1142/S0218194015400288  0.735
2015 Gao K, Khoshgoftaar TM, Napolitano A. Investigating two approaches for adding feature ranking to sampled ensemble learning for software quality estimation International Journal of Software Engineering and Knowledge Engineering. 25: 115-146. DOI: 10.1142/S0218194015400069  0.746
2015 Wang H, Khoshgoftaar TM, Napolitano A. An Empirical Investigation on Wrapper-Based Feature Selection for Predicting Software Quality International Journal of Software Engineering and Knowledge Engineering. 25: 93-114. DOI: 10.1142/S0218194015400057  0.675
2015 Richter AN, Khoshgoftaar TM, Landset S, Hasanin T. A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data Proceedings - 2015 Ieee 16th International Conference On Information Reuse and Integration, Iri 2015. 1-8. DOI: 10.1109/IRI.2015.12  0.326
2015 Zuech R, Khoshgoftaar TM. A survey on feature selection for intrusion detection Proceedings - 21st Issat International Conference On Reliability and Quality in Design. 150-155.  0.324
2015 Najafabadi MM, Khoshgoftaar TM, Napolitano A. A comparison of feature selection strategies for identifying malicious network sessions Proceedings - 21st Issat International Conference On Reliability and Quality in Design. 161-167.  0.305
2014 Herland M, Khoshgoftaar TM, Wald R. A review of data mining using big data in health informatics Journal of Big Data. 1: 2. DOI: 10.1186/2196-1115-1-2  0.793
2014 Gao K, Khoshgoftaar TM, Wald R. The use of under- and oversampling within ensemble feature selection and classification for software quality prediction International Journal of Reliability, Quality and Safety Engineering. 21. DOI: 10.1142/S0218539314500041  0.851
2014 Gao K, Khoshgoftaar TM, Napolitano A. The Use of Ensemble-Based Data Preprocessing Techniques for Software Defect Prediction International Journal of Software Engineering and Knowledge Engineering. 24: 1229-1253. DOI: 10.1142/S0218194014400105  0.751
2014 Najafabadi MM, Khoshgoftaar TM, Kemp C, Seliya N, Zuech R. Machine learning for detecting brute force attacks at the network level Proceedings - Ieee 14th International Conference On Bioinformatics and Bioengineering, Bibe 2014. 379-385. DOI: 10.1109/BIBE.2014.73  0.608
2014 Seiffert C, Khoshgoftaar TM, Van Hulse J, Folleco A. An empirical study of the classification performance of learners on imbalanced and noisy software quality data Information Sciences. 259: 571-595. DOI: 10.1016/J.Ins.2010.12.016  0.744
2014 Khoshgoftaar TM, Xiao Y, Gao K. Software quality assessment using a multi-strategy classifier Information Sciences. 259: 555-570. DOI: 10.1016/J.Ins.2010.11.028  0.721
2014 Xu Z, Gao K, Khoshgoftaar TM, Seliya N. System regression test planning with a fuzzy expert system Information Sciences. 259: 532-543. DOI: 10.1016/J.Ins.2010.09.012  0.745
2014 Khoshgoftaar TM, Wang H, Seliya N. Performance of filter-based feature subset selection for software quality data classification Rqd 2014 - Proceedings - 20th Issat International Conference Reliability and Quality in Design. 218-222.  0.731
2013 WINTER V, CUKIC B, KHOSHGOFTAAR T, MORI K, PAUL R, PÉREZ-LEGUÍZAMO C, SEDIGH SARVESTANI S, SLOAN JC, VOUK M, YEN I. HIGH CONSEQUENCE SYSTEMS AND SEMANTIC COMPUTING International Journal of Semantic Computing. 7: 291-324. DOI: 10.1142/S1793351X13500050  0.668
2013 Wald R, Khoshgoftaar TM, Sloan JC. Feature selection for optimization of wavelet packet decomposition in reliability analysis of systems International Journal On Artificial Intelligence Tools. 22. DOI: 10.1142/S0218213013600117  0.813
2013 WANG H, KHOSHGOFTAAR TM, LIANG Q(. A STUDY OF SOFTWARE METRIC SELECTION TECHNIQUES: STABILITY ANALYSIS AND DEFECT PREDICTION MODEL PERFORMANCE International Journal On Artificial Intelligence Tools. 22: 1360010. DOI: 10.1142/S0218213013600105  0.487
2013 Wang H, Khoshgoftaar TM, Napolitano A. An empirical study on wrapper-based feature selection for software engineering data Proceedings - 2013 12th International Conference On Machine Learning and Applications, Icmla 2013. 2: 84-89. DOI: 10.1109/ICMLA.2013.110  0.635
2013 Seliya N, Khoshgoftaar TM. Software quality analysis with distribution bias in defect data Proceedings - 19th Issat International Conference On Reliability and Quality in Design, Rqd 2013. 225-229.  0.722
2013 Gao K, Khoshgoftaar TM, Napolitano A. Exploring ensemble-based data preprocessing techniques for software quality estimation Proceedings of the International Conference On Software Engineering and Knowledge Engineering, Seke. 2013: 612-617.  0.447
2013 Gao K, Khoshgoftaar TM, Wald R. A comparative study of iterative feature selection and boosting for software quality estimation Proceedings - 19th Issat International Conference On Reliability and Quality in Design, Rqd 2013. 230-234.  0.446
2012 Gao K, Khoshgoftaar TM, Wang H. Exploring filter-based feature selection techniques for software quality classification International Journal of Information and Decision Sciences. 4: 217-250. DOI: 10.1504/Ijids.2012.047074  0.656
2012 Shanab AA, Khoshgoftaar TM, Wald R, Van Hulse J. Evaluation of the importance of data pre-processing order when combining feature selection and data sampling International Journal of Business Intelligence and Data Mining. 7: 116-134. DOI: 10.1504/Ijbidm.2012.048730  0.817
2012 Altidor W, Khoshgoftaar TM, Napolitano A. Measuring stability of feature ranking techniques: A noise-based approach International Journal of Business Intelligence and Data Mining. 7: 80-115. DOI: 10.1504/Ijbidm.2012.048729  0.82
2012 Wald R, Khoshgoftaar TM, Alhalabi B. Baseline-differencing: A novel approach for building generalizable ocean turbine reliability models International Journal of Reliability, Quality and Safety Engineering. 19. DOI: 10.1142/S0218539312400050  0.805
2012 KHOSHGOFTAAR TM, GAO K, NAPOLITANO A. AN EMPIRICAL STUDY OF FEATURE RANKING TECHNIQUES FOR SOFTWARE QUALITY PREDICTION International Journal of Software Engineering and Knowledge Engineering. 22: 161-183. DOI: 10.1142/S0218194012400013  0.744
2012 Duhaney J, Khoshgoftaar TM, Wald R. Applying feature selection to short time wavelet transformed vibration data for reliability analysis of an ocean turbine Proceedings - 2012 11th International Conference On Machine Learning and Applications, Icmla 2012. 1: 330-337. DOI: 10.1109/ICMLA.2012.62  0.355
2012 Wang H, Khoshgoftaar TM, Napolitano A. An empirical study on the stability of feature selection for imbalanced software engineering data Proceedings - 2012 11th International Conference On Machine Learning and Applications, Icmla 2012. 1: 317-323. DOI: 10.1109/ICMLA.2012.60  0.611
2012 Wang H, Khoshgoftaar TM, Napolitano A. Software measurement data reduction using ensemble techniques Neurocomputing. 92: 124-132. DOI: 10.1016/J.Neucom.2011.08.040  0.673
2012 Van Hulse J, Khoshgoftaar TM, Napolitano A, Wald R. Threshold-based feature selection techniques for high-dimensional bioinformatics data Network Modeling Analysis in Health Informatics and Bioinformatics. 1: 47-61. DOI: 10.1007/S13721-012-0006-6  0.818
2012 Gao K, Khoshgoftaar TM, Seliya N. Predicting high-risk program modules by selecting the right software measurements Software Quality Journal. 20: 3-42. DOI: 10.1007/S11219-011-9132-0  0.781
2011 Van Hulse J, Khoshgoftaar TM, Napolitano A. An exploration of learning when data is noisy and imbalanced Intelligent Data Analysis. 15: 215-236. DOI: 10.3233/IDA-2010-0464  0.734
2011 Van Hulse J, Khoshgoftaar TM, Napolitano A. Evaluating the impact of data quality on sampling Journal of Information and Knowledge Management. 10: 225-245. DOI: 10.1142/S021964921100295X  0.756
2011 Khoshgoftaar TM, Gao K, Bullard LA. A Comparative study of filter-based and wrapper-based feature ranking techniques for software quality modeling International Journal of Reliability, Quality and Safety Engineering. 18: 341-364. DOI: 10.1142/S0218539311004287  0.841
2011 Sloan JC, Khoshgoftaar TM, Alhalabi B, Beaujean PP. Strategy and application of data-driven testing of an ocean turbine drivetrain International Journal of Reliability, Quality and Safety Engineering. 18: 555-571. DOI: 10.1142/S021853931100424X  0.71
2011 Wang H, Khoshgoftaar TM, Van Hulse J, Gao K. Metric selection for software defect prediction International Journal of Software Engineering and Knowledge Engineering. 21: 237-257. DOI: 10.1142/S0218194011005256  0.785
2011 Khoshgoftaar TM, Van Hulse J, Napolitano A. Comparing boosting and bagging techniques with noisy and imbalanced data Ieee Transactions On Systems, Man, and Cybernetics Part a:Systems and Humans. 41: 552-568. DOI: 10.1109/TSMCA.2010.2084081  0.772
2011 Wald R, Khoshgoftaar T, Sloan JC. Fourier transforms for vibration analysis: A review and case study Proceedings of the 2011 Ieee International Conference On Information Reuse and Integration, Iri 2011. 366-371. DOI: 10.1109/IRI.2011.6009575  0.641
2011 Van Hulse J, Khoshgoftaar TM, Napolitano A. A comparative evaluation of feature ranking methods for high dimensional bioinformatics data Proceedings of the 2011 Ieee International Conference On Information Reuse and Integration, Iri 2011. 315-320. DOI: 10.1109/IRI.2011.6009566  0.763
2011 Wang H, Khoshgoftaar TM, Wald R. Measuring robustness of Feature Selection techniques on software engineering datasets Proceedings of the 2011 Ieee International Conference On Information Reuse and Integration, Iri 2011. 309-314. DOI: 10.1109/IRI.2011.6009565  0.33
2011 Altidor W, Khoshgoftaar TM, Napolitano A. A noise-based stability evaluation of threshold-based feature selection techniques Proceedings of the 2011 Ieee International Conference On Information Reuse and Integration, Iri 2011. 240-245. DOI: 10.1109/IRI.2011.6009553  0.808
2011 Shanab AA, Khoshgoftaar TM, Wald R, Van Hulse J. Comparison of approaches to alleviate problems with high-dimensional and class-imbalanced data Proceedings of the 2011 Ieee International Conference On Information Reuse and Integration, Iri 2011. 234-239. DOI: 10.1109/IRI.2011.6009552  0.702
2011 Duhaney J, Khoshgoftaar TM, Sloan JC. Feature selection on dynamometer data for reliability analysis Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 1012-1019. DOI: 10.1109/ICTAI.2011.173  0.728
2011 Wang H, Khoshgoftaar TM. Measuring stability of threshold-based feature selection techniques Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 986-993. DOI: 10.1109/ICTAI.2011.169  0.332
2011 Wald R, Khoshgoftaar TM, Sloan JC. Feature selection for vibration sensor data transformed by a streaming wavelet packet decomposition Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 978-985. DOI: 10.1109/ICTAI.2011.168  0.702
2011 Duhaney J, Khoshgoftaar TM, Sloan JC, Alhalabi B, Beaujean PP. A dynamometer for an ocean turbine prototype - Reliability through automated monitoring Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 244-251. DOI: 10.1109/HASE.2011.61  0.702
2011 Wald R, Khoshgoftaar TM, Sloan JC. Using feature selection to determine optimal depth forwavelet packet decomposition of vibration signals for ocean system reliability Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 236-243. DOI: 10.1109/HASE.2011.60  0.705
2011 Sloan JC, Khoshgoftaar TM. Ensemble coordination for discrete event control Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 227-235. DOI: 10.1109/HASE.2011.26  0.682
2011 Seliya N, Khoshgoftaar TM. The use of decision trees for cost-sensitive classification: An empirical study in software quality prediction Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 1: 448-459. DOI: 10.1002/Widm.38  0.703
2011 Gao K, Khoshgoftaar TM, Wang H, Seliya N. Choosing software metrics for defect prediction: An investigation on feature selection techniques Software - Practice and Experience. 41: 579-606. DOI: 10.1002/Spe.1043  0.785
2011 Gao K, Khoshgoftaar TM. Exploring several strategies to improve software quality prediction Proceedings - 17th Issat International Conference On Reliability and Quality in Design. 325-329.  0.444
2011 Gao K, Khoshgoftaar TM. Software defect prediction for high-dimensional and class-imbalanced data Seke 2011 - Proceedings of the 23rd International Conference On Software Engineering and Knowledge Engineering. 89-94.  0.428
2011 Sloan JC, Khoshgoftaar TM, Alhalabi B. A strategy for data-driven testing of an ocean turbine drivetrain Proceedings - 17th Issat International Conference On Reliability and Quality in Design. 364-368.  0.668
2011 Altidor W, Khoshgoftaar TM, Van Hulse J. Robustness of filter-based feature ranking: A case study Proceedings of the 24th International Florida Artificial Intelligence Research Society, Flairs - 24. 453-458.  0.797
2010 Khoshgoftaar TM, Van Hulse J, Napolitano A. Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 21: 813-30. PMID 20236881 DOI: 10.1109/Tnn.2010.2042730  0.745
2010 Qian L, Yao Q, Khoshgoftaar TM. Dynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software Journal of Software Engineering and Applications. 3: 603-609. DOI: 10.4236/Jsea.2010.36070  0.367
2010 Khoshgoftaar TM, Seliya N, Drown DJ. Evolutionary data analysis for the class imbalance problem Intelligent Data Analysis. 14: 69-88. DOI: 10.3233/IDA-2010-0409  0.696
2010 Altidor W, Khoshgoftaar TM, Gao K. Wrapper-based feature ranking techniques for determining relevance of software engineering metrics International Journal of Reliability, Quality and Safety Engineering. 17: 425-464. DOI: 10.1142/S0218539310003883  0.837
2010 Van Hulse J, Khoshgoftaar TM, Napolitano A. An empirical evaluation of repetitive undersampling techniques International Journal of Software Engineering and Knowledge Engineering. 20: 173-195. DOI: 10.1142/S0218194010004682  0.753
2010 Seiffert C, Khoshgoftaar TM, Van Hulse J, Napolitano A. RUSBoost: A hybrid approach to alleviating class imbalance Ieee Transactions On Systems, Man, and Cybernetics Part a:Systems and Humans. 40: 185-197. DOI: 10.1109/TSMCA.2009.2029559  0.759
2010 Liu Y, Khoshgoftaar TM, Seliya N. Evolutionary optimization of software quality modeling with multiple repositories Ieee Transactions On Software Engineering. 36: 852-864. DOI: 10.1109/Tse.2010.51  0.736
2010 Seliya N, Khoshgoftaar TM. Active learning with neural networks for intrusion detection 2010 Ieee International Conference On Information Reuse and Integration, Iri 2010. 49-54. DOI: 10.1109/IRI.2010.5558967  0.669
2010 Khoshgoftaar TM, Gao K, Van Hulse J. A novel feature selection technique for highly imbalanced data 2010 Ieee International Conference On Information Reuse and Integration, Iri 2010. 80-85. DOI: 10.1109/IRI.2010.5558961  0.727
2010 Khoshgoftaar TM, Gao K, Seliya N. Attribute selection and imbalanced data: Problems in software defect prediction Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 1: 137-144. DOI: 10.1109/ICTAI.2010.27  0.736
2010 Van Hulse J, Khoshgoftaar TM, Napolitano A. A novel noise filtering algorithm for imbalanced data Proceedings - 9th International Conference On Machine Learning and Applications, Icmla 2010. 9-14. DOI: 10.1109/ICMLA.2010.9  0.726
2010 Dittman DJ, Khoshgoftaar TM, Wald R, Van Hulse J. Comparative analysis of DNA microarray data through the use of feature selection techniques Proceedings - 9th International Conference On Machine Learning and Applications, Icmla 2010. 147-152. DOI: 10.1109/ICMLA.2010.29  0.623
2010 Seliya N, Khoshgoftaar TM, Van Hulse J. Predicting faults in high assurance software Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 26-34. DOI: 10.1109/HASE.2010.29  0.81
2010 Wang H, Khoshgoftaar TM, Van Hulse J. A comparative study of threshold-based feature selection techniques Proceedings - 2010 Ieee International Conference On Granular Computing, Grc 2010. 499-504. DOI: 10.1109/GrC.2010.104  0.735
2010 Khoshgoftaar TM, Gao K. A novel software metric selection technique using the area under ROC curves Seke 2010 - Proceedings of the 22nd International Conference On Software Engineering and Knowledge Engineering. 203-208.  0.438
2010 Seliya N, Khoshgoftaar TM. SOftware defect prediction with skewed data Proceedings - 16th Issat International Conference On Reliability and Quality in Design. 403-407.  0.711
2010 Wang H, Khoshgoftaar TM, Gao K. Ensemble feature selection technique for software quality classification Seke 2010 - Proceedings of the 22nd International Conference On Software Engineering and Knowledge Engineering. 215-220.  0.429
2009 Seiffert C, Khoshgoftaar TM, Van Hulse J. Hybrid sampling for imbalanced data Integrated Computer-Aided Engineering. 16: 193-210. DOI: 10.3233/ICA-2009-0314  0.676
2009 Su X, Khoshgoftaar TM, Greiner R. Making an accurate classifier ensemble by voting on classifications from imputed learning sets International Journal of Information and Decision Sciences. 1: 301-322. DOI: 10.1504/Ijids.2009.027657  0.631
2009 Su X, Khoshgoftaar TM. A Survey of Collaborative Filtering Techniques Advances in Artificial Intelligence. 2009: 1-19. DOI: 10.1155/2009/421425  0.556
2009 Sloan JC, Khoshgoftaar TM, Beaujean PP, Driscoll F. Ocean turbines - A reliability assessment International Journal of Reliability, Quality and Safety Engineering. 16: 413-433. DOI: 10.1142/S0218539309003472  0.693
2009 Sloan JC, Khoshgoftaar TM. Testing and Formal Verification of Service Oriented Architectures International Journal of Reliability, Quality and Safety Engineering. 16: 137-162. DOI: 10.1142/S0218539309003332  0.703
2009 Khoshgoftaar TM, Bullard LA, Gao K. Attribute selection using rough sets in software quality classification International Journal of Reliability, Quality and Safety Engineering. 16: 73-89. DOI: 10.1142/S0218539309003307  0.834
2009 Seiffert C, Khoshgoftaar TM, Van Hulse J. Improving software-quality predictions with data sampling and boosting Ieee Transactions On Systems, Man, and Cybernetics Part a:Systems and Humans. 39: 1283-1294. DOI: 10.1109/TSMCA.2009.2027131  0.732
2009 Drown DJ, Khoshgoftaar TM, Seliya N. Evolutionary sampling and software quality modeling of high-assurance systems Ieee Transactions On Systems, Man, and Cybernetics Part a:Systems and Humans. 39: 1097-1107. DOI: 10.1109/TSMCA.2009.2020804  0.714
2009 Sloan JC, Khoshgoftaar TM. From Web service artifact to a readable and verifiable model Ieee Transactions On Services Computing. 2: 277-288. DOI: 10.1109/Tsc.2009.23  0.692
2009 Van Hulse J, Khoshgoftaar TM, Napolitano A. An empirical comparison of repetitive undersampling techniques 2009 Ieee International Conference On Information Reuse and Integration, Iri 2009. 29-34. DOI: 10.1109/IRI.2009.5211614  0.754
2009 Seliya N, Khoshgoftaar TM, Van Hulse J. Aggregating performance metrics for classifier evaluation 2009 Ieee International Conference On Information Reuse and Integration, Iri 2009. 35-40. DOI: 10.1109/IRI.2009.5211611  0.779
2009 Altidor W, Khoshgoftaar TM, Van Hulse J. An empirical study on wrapper-based feature ranking Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 75-82. DOI: 10.1109/ICTAI.2009.29  0.819
2009 Seliya N, Khoshgoftaar TM, Van Hulse J. A study on the relationships of classifier performance metrics Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 59-66. DOI: 10.1109/ICTAI.2009.25  0.791
2009 Wang H, Khoshgoftaar TM, Gao K, Seliya N. High-dimensional software engineering data and feature selection Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 83-90. DOI: 10.1109/ICTAI.2009.20  0.724
2009 Khoshgoftaar TM, Gao K. Feature selection with imbalanced data for software defect prediction 8th International Conference On Machine Learning and Applications, Icmla 2009. 235-240. DOI: 10.1109/ICMLA.2009.18  0.392
2009 Altidor W, Khoshgoftaar TM, Napolitano A. Wrapper-based feature ranking for software engineering metrics 8th International Conference On Machine Learning and Applications, Icmla 2009. 241-246. DOI: 10.1109/ICMLA.2009.17  0.824
2009 Wang H, Khoshgoftaar TM, Gao K, Seliya N. Mining data from multiple software development projects Icdm Workshops 2009 - Ieee International Conference On Data Mining. 551-557. DOI: 10.1109/ICDMW.2009.78  0.713
2009 Van Hulse J, Khoshgoftaar TM, Napolitano A, Wald R. Feature selection with high-dimensional imbalanced data Icdm Workshops 2009 - Ieee International Conference On Data Mining. 507-514. DOI: 10.1109/ICDMW.2009.35  0.735
2009 Van Hulse J, Khoshgoftaar T. Knowledge discovery from imbalanced and noisy data Data and Knowledge Engineering. 68: 1513-1542. DOI: 10.1016/j.datak.2009.08.005  0.683
2009 Khoshgoftaar TM, Rebours P, Seliya N. Software quality analysis by combining multiple projects and learners Software Quality Journal. 17: 25-49. DOI: 10.1007/S11219-008-9058-3  0.723
2009 Seliya N, Khoshgoftaar TM. Cost-based fault prediction models Proceedings - 15th Issat International Conference On Reliability and Quality in Design. 352-356.  0.675
2009 Seliya N, Khoshgoftaar TM. Value-based software quality modeling Proceedings of the 21st International Conference On Software Engineering and Knowledge Engineering, Seke 2009. 116-121.  0.692
2009 Lin P, Wang H, Khoshgoftaar TM. A novel hybrid search algorithm for feature selection Proceedings of the 21st International Conference On Software Engineering and Knowledge Engineering, Seke 2009. 81-86.  0.339
2009 Sloan JC, Khoshgoftaar TM, Varas A. An extendible translation of BPEL to a machine-verifiable model Proceedings of the 21st International Conference On Software Engineering and Knowledge Engineering, Seke 2009. 344-349.  0.673
2008 Khoshgoftaar TM, Bullard LA, Gao K. A rule-based software quality classification model International Journal of Reliability, Quality and Safety Engineering. 15: 247-259. DOI: 10.1142/S0218539308003064  0.826
2008 Su X, Khoshgoftaar TM. Collaborative filtering for multi-class data using bayesian networks International Journal On Artificial Intelligence Tools. 17: 71-85. DOI: 10.1142/S0218213008003789  0.616
2008 Sloan JC, Khoshgoftaar TM, Raghav V. Assuring timeliness in an e-Science service-oriented architecture Computer. 41: 56-62. DOI: 10.1109/Mc.2008.313  0.663
2008 Folleco A, Khoshgoftaar TM, Van Hulse J, Bullard L. Identifying learners robust to low quality data 2008 Ieee International Conference On Information Reuse and Integration, Ieee Iri-2008. 190-195. DOI: 10.1109/IRI.2008.4583028  0.676
2008 Seiffert C, Khoshgoftaar TM, Van Hulse J, Napolitano A. Resampling or reweighting: A comparison of boosting implementations Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 1: 445-451. DOI: 10.1109/ICTAI.2008.59  0.733
2008 Seliya N, Xu Z, Khoshgoftaar TM. Addressing class imbalance in non-binary classification problems Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 1: 460-466. DOI: 10.1109/ICTAI.2008.120  0.688
2008 Seiffert C, Khoshgoftaar TM, Van Hulse J, Napolitano A. A comparative study of data sampling and cost sensitive learning Proceedings - Ieee International Conference On Data Mining Workshops, Icdm Workshops 2008. 46-52. DOI: 10.1109/ICDMW.2008.119  0.732
2008 Folleco A, Khoshgoftaar TM, Van Hulse J, Bullard L. Software quality modeling: The impact of class noise on the random forest classifier 2008 Ieee Congress On Evolutionary Computation, Cec 2008. 3853-3859. DOI: 10.1109/CEC.2008.4631321  0.678
2008 Van Hulse J, Khoshgoftaar TM. A comprehensive empirical evaluation of missing value imputation in noisy software measurement data Journal of Systems and Software. 81: 691-708. DOI: 10.1016/J.Jss.2007.07.043  0.735
2008 Khoshgoftaar TM, Van Hulse J. Imputation techniques for multivariate missingness in software measurement data Software Quality Journal. 16: 563-600. DOI: 10.1007/s11219-008-9054-7  0.68
2008 Folleco A, Khoshgoftaar TM, Van Hulse J. Software fault imputation in noisy and incomplete measurement data Springer Series in Reliability Engineering. 18: 255-274. DOI: 10.1007/978-1-84800-113-8_12  0.648
2008 Sloan JC, Khoshgoftaar TM. Toward model checking web services over the web 20th International Conference On Software Engineering and Knowledge Engineering, Seke 2008. 519-524.  0.648
2008 Sloan JC, Khoshgoftaar TM. Tradeoffs in testing service oriented architectures Proceedings - 14th Issat International Conference On Reliability and Quality in Design. 141-145.  0.656
2008 Seliya N, Khoshgoftaar TM. Software quality modeling and estimation with missing data International Journal of Performability Engineering. 4: 5-18.  0.707
2008 Seliya N, Khoshgoftaar TM. Addressing class imbalance in software quality modeling Proceedings - 14th Issat International Conference On Reliability and Quality in Design. 137-140.  0.73
2008 Sloan JC, Khoshgoftaar TM, Folleco A. Testingweb services as agents Proceedings - 14th Issat International Conference On Reliability and Quality in Design. 151-155.  0.633
2008 Folleco AA, Khoshgoftaar TM, Bullard LA. Analyzing the impact of attribute noise on software quality classification 20th International Conference On Software Engineering and Knowledge Engineering, Seke 2008. 73-78.  0.796
2007 Seliya N, Khoshgoftaar TM. Software quality modeling with limited apriori defect data Knowledge Discovery and Data Mining: Challenges and Realities. 1-15. DOI: 10.4018/978-1-59904-252-7.ch001  0.714
2007 Khoshgoftaar TM, Van Hulse J, Seiffert C, Zhao L. The multiple imputation quantitative noise corrector Intelligent Data Analysis. 11: 245-263. DOI: 10.3233/ida-2007-11303  0.595
2007 Van Hulse J, Khoshgoftaar TM, Napolitano A. Experimental perspectives on learning from imbalanced data Acm International Conference Proceeding Series. 227: 935-942. DOI: 10.1145/1273496.1273614  0.731
2007 Zhong S, Khoshgoftaar TM, Seliya N. Clustering-based network intrusion detection International Journal of Reliability, Quality and Safety Engineering. 14: 169-187. DOI: 10.1142/S0218539307002568  0.637
2007 Khoshgoftaar TM, Seiffert C, Seliya N. Low-effort labeling of network events for intrusion detection in WLANs Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, Flairs 2007. 490-495. DOI: 10.1142/S0218213008004035  0.679
2007 Seliya N, Khoshgoftaar TM. Software quality analysis of unlabeled program modules with semisupervised clustering Ieee Transactions On Systems, Man, and Cybernetics Part a:Systems and Humans. 37: 201-211. DOI: 10.1109/TSMCA.2006.889473  0.702
2007 Khoshgoftaar TM, Liu Y. A multi-objective software quality classification model using genetic programming Ieee Transactions On Reliability. 56: 237-245. DOI: 10.1109/Tr.2007.896763  0.458
2007 Gao K, Khoshgoftaar TM. A comprehensive empirical study of count models for software fault prediction Ieee Transactions On Reliability. 56: 223-236. DOI: 10.1109/Tr.2007.896761  0.447
2007 Khoshgoftaar TM, Gao K. Count models for software quality estimation Ieee Transactions On Reliability. 56: 212-222. DOI: 10.1109/Tr.2007.896757  0.464
2007 Luo Q, Khoshgoftaar TM. An empirical study on estimating motions in video stabilization 2007 Ieee International Conference On Information Reuse and Integration, Ieee Iri-2007. 360-366. DOI: 10.1109/IRI.2007.4296647  0.351
2007 Seiffert C, Khoshgoftaar TM, Van Hulse J, Napolitano A. Mining data with rare events: A case study Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 2: 132-139. DOI: 10.1109/ICTAI.2007.71  0.742
2007 Khoshgoftaar TM, Golawala M, Van Hulse J. An empirical study of learning from imbalanced data using random forest Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 2: 310-317. DOI: 10.1109/ICTAI.2007.46  0.657
2007 Khoshgoftaar TM, Seiffert C, Van Hulse J, Napolitano A, Folleco A. Learning with limited minority class data Proceedings - 6th International Conference On Machine Learning and Applications, Icmla 2007. 348-353. DOI: 10.1109/ICMLA.2007.64  0.736
2007 Bullard LA, Khoshgoftaar TM, Kehan G. An Application of a rule-based model in software quality classification Proceedings - 6th International Conference On Machine Learning and Applications, Icmla 2007. 204-210. DOI: 10.1109/ICMLA.2007.14  0.794
2007 Van Hulse J, Khoshgoftaar TM, Napolitano A. Skewed class distributions and mislabeled examples Proceedings - Ieee International Conference On Data Mining, Icdm. 477-482. DOI: 10.1109/ICDMW.2007.34  0.723
2007 Van Hulse J, Khoshgoftaar TM. Incomplete-case nearest neighbor imputation in software measurement data 2007 Ieee International Conference On Information Reuse and Integration, Ieee Iri-2007. 630-637. DOI: 10.1016/J.Ins.2010.12.017  0.692
2007 Khoshgoftaar TM, Rebours P. Improving software quality prediction by noise filtering techniques Journal of Computer Science and Technology. 22: 387-396. DOI: 10.1007/S11390-007-9054-2  0.371
2007 Seliya N, Khoshgoftaar TM. Software quality estimation with limited fault data: a semi-supervised learning perspective Software Quality Journal. 15: 327-344. DOI: 10.1007/S11219-007-9013-8  0.725
2007 Zhu X, Khoshgoftaar TM, Davidson I, Zhang S. Editorial: Special issue on mining low-quality data Knowledge and Information Systems. 11: 131-136. DOI: 10.1007/S10115-006-0058-Y  0.387
2007 Khoshgoftaar TM, Seliya N. Ordinal classification for intrusion detection in wireless networks: An empirical evaluation Proceedings - 13th Issat International Conference On Reliability and Quality in Design. 175-180.  0.672
2007 Van Hulse J, Khoshgoftaar TM, Napolitano A. Software reliability modeling using skewed measurement data Proceedings - 13th Issat International Conference On Reliability and Quality in Design. 181-185.  0.763
2007 Folleco A, Khoshgoftaar TM, Van Hulse J. Software quality classification with imbalanced and noisy data Proceedings - 13th Issat International Conference On Reliability and Quality in Design. 191-195.  0.702
2006 Luo Q, Khoshgoftaar TM. Unsupervised multiscale color image segmentation based on MDL principle. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 15: 2755-61. PMID 16948319 DOI: 10.1109/TIP.2006.877342  0.401
2006 Liu Y, Khoshgoftaar TM. A practical software quality classification model using genetic programming Advances in Machine Learning Applications in Software Engineering. 208-236. DOI: 10.4018/978-1-59140-941-1.ch009  0.336
2006 Khoshgoftaar TM, Rebours P. Noise elimination with partitioning filter for software quality estimation International Journal of Computer Applications in Technology. 27: 246-258. DOI: 10.1504/Ijcat.2006.011996  0.377
2006 Khoshgoftaar TM, Gao K, Lin H. Indirect classification approaches: A comparative study in network intrusion detection International Journal of Computer Applications in Technology. 27: 232-245. DOI: 10.1504/Ijcat.2006.011995  0.607
2006 Khoshgoftaar TM, Szabo RM. Dynamic models for testing based on time series analysis International Journal of Reliability, Quality and Safety Engineering. 13: 581-597. DOI: 10.1142/S0218539306002434  0.433
2006 FOLLECO A, KHOSHGOFTAAR T. ATTRIBUTE NOISE DETECTION USING MULTI-RESOLUTION ANALYSIS International Journal of Reliability, Quality and Safety Engineering. 13: 267-288. DOI: 10.1142/S0218539306002252  0.421
2006 Khoshgoftaar TM, Folleco A, Van Hulse J, Bullard L. Software quality imputation in the presence of noisy data Proceedings of the 2006 Ieee International Conference On Information Reuse and Integration, Iri-2006. 484-489. DOI: 10.1109/IRI.2006.252462  0.704
2006 Van Hulse J, Khoshgoftaar TM, Seiffert C, Zhao L. Noise correction using Bayesian multiple imputation Proceedings of the 2006 Ieee International Conference On Information Reuse and Integration, Iri-2006. 478-483. DOI: 10.1109/IRI.2006.252461  0.634
2006 Khoshgoftaar TM, Seiffert C, Seliya N. Labeling network event records for intrusion detection in a wireless LAN Proceedings of the 2006 Ieee International Conference On Information Reuse and Integration, Iri-2006. 200-206. DOI: 10.1109/IRI.2006.252413  0.659
2006 Khoshgoftaar TM, Van Hulse J, Seiffert C. A hybrid approach to cleansing software measurement data Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 713-722. DOI: 10.1109/ICTAI.2006.11  0.695
2006 Van Hulse J, Khoshgoftaar TM, Seiffert C. A comparison of software fault imputation procedures Proceedings - 5th International Conference On Machine Learning and Applications, Icmla 2006. 135-142. DOI: 10.1109/ICMLA.2006.5  0.685
2006 Rebours P, Khoshgoftaar TM. Quality Problem in Software Measurement Data Advances in Computers. 66: 43-77. DOI: 10.1016/S0065-2458(05)66002-0  0.395
2006 Khoshgoftaar TM, Seliya N, Sundaresh N. An empirical study of predicting software faults with case-based reasoning Software Quality Journal. 14: 85-111. DOI: 10.1007/S11219-006-7597-Z  0.702
2006 Khoshgoftaar TM, Herzberg A, Seliya N. Resource oriented selection of rule-based classification models: An empirical case study Software Quality Journal. 14: 309-338. DOI: 10.1007/S11219-006-0038-1  0.735
2006 Khoshgoftaar TM, Van Hulse J. Multiple imputation of software measurement data: A case study 18th International Conference On Software Engineering and Knowledge Engineering, Seke 2006. 220-226.  0.689
2006 Seliya N, Khoshgoftaar TM. Software faults modeling with limited defect occurrence knowledge 2006 Proceedings - 12th Issat International Conference On Reliability and Quality in Design. 134-138.  0.7
2006 Khoshgoftaar TM, Seiffert C, Van Hulse J. Polishing noise in continuous software measurement data 18th International Conference On Software Engineering and Knowledge Engineering, Seke 2006. 227-231.  0.683
2006 Khoshgoftaar TM, Van Hulse J. Determining noisy instances relative to attributes of interest Intelligent Data Analysis. 10: 251-268.  0.687
2006 Van Hulse J, Khoshgoftaar TM. Class noise detection using frequent itemsets Intelligent Data Analysis. 10: 487-507.  0.689
2005 Luo Q, Khoshgoftaar TM, An E. Hierarchical indexing of ocean survey video by mean shift clustering and MDL principle Proceedings of the 2005 Ieee International Conference On Information Reuse and Integration, Iri - 2005. 2005: 404-409. DOI: 10.1109/IRI-05.2005.1506507  0.433
2005 Khoshgoftaar TM, Van Hulse J. Empirical case studies in attribute noise detection Proceedings of the 2005 Ieee International Conference On Information Reuse and Integration, Iri - 2005. 2005: 211-216. DOI: 10.1109/IRI-05.2005.1506475  0.678
2005 Xiao Y, Khoshgoftaar TM, Seliya N. The partitioning- And rule-based filter for noise detection Proceedings of the 2005 Ieee International Conference On Information Reuse and Integration, Iri - 2005. 2005: 205-210. DOI: 10.1109/IRI-05.2005.1506474  0.656
2005 Khoshgoftaar TM, Nath SV, Zhong S, Seliya N. Intrusion detection in wireless networks using clustering techniques with expert analysis Proceedings - Icmla 2005: Fourth International Conference On Machine Learning and Applications. 2005: 120-125. DOI: 10.1109/ICMLA.2005.43  0.613
2005 Khoshgoftaar TM, Van Hulse J. Identifying noise in an attribute of interest Proceedings - Icmla 2005: Fourth International Conference On Machine Learning and Applications. 2005: 55-60. DOI: 10.1109/ICMLA.2005.39  0.706
2005 Khoshgoftaar TM, Gao K, Szabo RM. Comparing software fault predictions of pure and zero-inflated Poisson regression models International Journal of Systems Science. 36: 705-715. DOI: 10.1080/00207720500159995  0.596
2005 Khoshgoftaar TM, Seliya N, Herzberg A. Resource-oriented software quality classification models Journal of Systems and Software. 76: 111-126. DOI: 10.1016/J.Jss.2004.04.027  0.711
2005 Khoshgoftaar TM, Seliya N, Gao K. Assessment of a new three-group software quality classification technique: An empirical case study Empirical Software Engineering. 10: 183-218. DOI: 10.1007/S10664-004-6191-X  0.702
2005 Seliya N, Khoshgoftaar TM. Software quality analysis in the absence of fault-proneness data 2005 Proceedings - 11th Issat International Conference On Reliability and Quality in Design. 101-105.  0.702
2005 Khoshgoftaar TM, Van Hulse J. Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm Intelligent Data Analysis. 9: 589-602.  0.629
2005 Khoshgoftaar TM, Seliya N, Gao K. Detecting noisy instances with the rule-based classification model Intelligent Data Analysis. 9: 347-364.  0.724
2005 Khoshgoftaar TM, Dong Y, Szabo RM. Software quality classification using Bayesian belief networks 2005 Proceedings - 11th Issat International Conference On Reliability and Quality in Design. 106-110.  0.362
2004 Szabo RM, Khoshgoftaar TM. Classifying software modules into three risk groups International Journal of Reliability, Quality and Safety Engineering. 11: 59-80. DOI: 10.1142/S0218539304001348  0.39
2004 Khoshgoftaar TM, Liu Y, Seliya N. A multiobjective module-order model for software quality enhancement Ieee Transactions On Evolutionary Computation. 8: 593-608. DOI: 10.1109/Tevc.2004.837108  0.717
2004 Zhong S, Khoshgoftaar TM, Seliya N. Analyzing Software Measurement Data with Clustering Techniques Ieee Intelligent Systems. 19: 20-27. DOI: 10.1109/Mis.2004.1274907  0.664
2004 Khoshgoftaar TM, Liu Y, Seliya N. Module-order modeling using an evolutionary multi-objective optimization approach Proceedings - International Software Metrics Symposium. 159-169. DOI: 10.1109/METRIC.2004.1357900  0.693
2004 Khoshgoftaar TM, Seliya N. The necessity of assuring quality in software measurement data Proceedings - International Software Metrics Symposium. 119-130. DOI: 10.1109/METRIC.2004.1357896  0.734
2004 Khoshgoftaar TM, Seliya N. Comparative assessment of software quality classification techniques: An empirical case study Empirical Software Engineering. 9: 229-257. DOI: 10.1023/B:Emse.0000027781.18360.9B  0.726
2004 Khoshgoftaar TM, Abushadi ME. Resource-sensitive intrusion detection models for network traffic Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 8: 249-258. DOI: 10.1016/S0065-2458(03)62006-1  0.361
2004 Xu Z, Khoshgoftaar TM. Identification of fuzzy models of software cost estimation Fuzzy Sets and Systems. 145: 141-163. DOI: 10.1016/J.Fss.2003.10.008  0.499
2004 Tang W, Khoshgoftaar TM. Noise identification with the k-means algorithm Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 373-378.  0.328
2004 Luo Q, Khoshgoftaar TM. Efficient image segmentation by mean shift clustering and MDL-guided region merging Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 337-343.  0.428
2004 Khoshgoftaar TM, Seliya N, Gao K. Rule-based noise detection for software measurement data Proceedings of the 2004 Ieee International Conference On Information Reuse and Integration, Iri-2004. 302-307.  0.703
2003 Khoshgoftaar TM, Geleyn E, Nguyen L. Empirical case studies of combining software quality classification models Proceedings - International Conference On Quality Software. 2003: 40-49. DOI: 10.1109/QSIC.2003.1319084  0.352
2003 Khoshgoftaar TM, Seliya N. Analogy-Based Practical Classification Rules for Software Quality Estimation Empirical Software Engineering. 8: 325-350. DOI: 10.1023/A:1025316301168  0.718
2003 Khoshgoftaar TM, Seliya N. Fault prediction modeling for software quality estimation: Comparing commonly used techniques Empirical Software Engineering. 8: 255-283. DOI: 10.1023/A:1024424811345  0.69
2003 Xu Z, Khoshgoftaar TM, Allen EB. Application of fuzzy expert systems in assessing operational risk of software Information and Software Technology. 45: 373-388. DOI: 10.1016/S0950-5849(03)00010-7  0.462
2003 Khoshgoftaar TM, Bullard LA, Gao K. Detecting outliers using rule-based modeling for improving cbr-based software quality classification models Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2689: 216-230. DOI: 10.1007/3-540-45006-8_19  0.824
2003 Liu Y, Khoshgoftaar TM. Building decision tree software quality classification models using genetic programming Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2724: 1808-1809.  0.342
2003 Khoshgoftaar TM, Liu Y, Seliya N. Genetic Programming-Based Decision Trees for Software Quality Classification Proceedings of the International Conference On Tools With Artificial Intelligence. 374-383.  0.668
2002 Khoshgoftaar TM, Allen EB. Predicting fault-prone software modules in embedded systems with classification trees International Journal of Reliability, Quality and Safety Engineering. 9: 1-16. DOI: 10.1142/S0218539302000639  0.373
2002 Khoshgoftaar TM, Seliya N. Software quality classification modeling using the SPRINT decision tree algorithm Proceedings of the International Conference On Tools With Artificial Intelligence. 365-374. DOI: 10.1142/S0218213003001204  0.709
2002 Khoshgoftaar TM, Cukic B, Seliya N. Predicting fault-prone modules in embedded systems using analogy-based classification models International Journal of Software Engineering and Knowledge Engineering. 12: 201-221. DOI: 10.1142/S0218194002000883  0.683
2002 Khoshgoftaar TM, Allen EB, Deng J. Using regression trees to classify fault-prone software modules Ieee Transactions On Reliability. 51: 455-462. DOI: 10.1109/Tr.2002.804488  0.385
2002 Khoshgoftaar TM, Seliya N. Tree-based software quality estimation models for fault prediction Proceedings - International Software Metrics Symposium. 2002: 203-214. DOI: 10.1109/METRIC.2002.1011339  0.687
2002 Khoshgoftaar TM, Seliya N. Improving usefulness of software quality classification models based on Boolean discriminant functions Proceedings - International Symposium On Software Reliability Engineering, Issre. 2002: 221-230. DOI: 10.1109/ISSRE.2002.1173256  0.719
2002 Khoshgoftaar TM, Yuan X, Allen EB, Jones WD, Hudepohl JP. Uncertain classification of fault-prone software modules Empirical Software Engineering. 7: 297-318. DOI: 10.1023/A:1020511004267  0.472
2001 Liu Y, Khoshgoftaar TM. Genetic programming model for software quality classification Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 2001: 127-136. DOI: 10.1109/HASE.2001.966814  0.306
2001 Xu Z, Khoshgoftaar TM. Software quality prediction for high-assurance network telecommunications systems Computer Journal. 44: 558-568. DOI: 10.1093/Comjnl/44.6.557  0.544
2001 Khoshgoftaar TM, Allen EB. Empirical Assessment of a Software Metric: The Information Content of Operators Software Quality Journal. 9: 99-112. DOI: 10.1023/A:1016622818771  0.379
2001 Khoshgoftaar TM, Allen EB, Jones WD, Hudepohl JP. Data Mining of Software Development Databases Software Quality Journal. 9: 161-176. DOI: 10.1023/A:1013349419545  0.331
2001 Khoshgoftaar TM, Allen EB. Controlling overfitting in classification-tree models of software quality Empirical Software Engineering. 6: 59-79. DOI: 10.1023/A:1009803004576  0.47
2000 Ganesan K, Khoshgoftaar TM, Allen EB. Case-based software quality prediction International Journal of Software Engineering and Knowledge Engineering. 10: 139-152. DOI: 10.1142/S0218194000000092  0.434
2000 Khoshgoftaar TM, Allen EB, Busboom JC. Modeling software quality: The Software Measurement Analysis and Reliability Toolkit Proceedings - International Conference On Tools With Artificial Intelligence, Ictai. 2000: 54-61. DOI: 10.1109/TAI.2000.889846  0.347
2000 Khoshgoftaar TM, Shan R, Allen EB. Using product, process, and execution metrics to predict fault-prone software modules with classification trees Proceedings of Ieee International Symposium On High Assurance Systems Engineering. 2000: 301-310. DOI: 10.1109/HASE.2000.895475  0.312
2000 Khoshgoftaar TM, Allen EB. A practical classification-rule for software-quality models Ieee Transactions On Reliability. 49: 209-216. DOI: 10.1109/24.877340  0.35
2000 Khoshgoftaar TM, Alien EB, Jones WD, Hudepohl JP. Classification-tree models of software-quality over multiple releases Ieee Transactions On Reliability. 49: 4-11. DOI: 10.1109/24.855532  0.306
2000 Khoshgoftaar TM, Allen EB, Jones WD, Hudepohl JP. Annals of Software Engineering. 9: 103-116. DOI: 10.1023/A:1018972607783  0.42
2000 Khoshgoftaar TM, Yuan X, Allen EB. Balancing misclassification rates in classification-tree models of software quality Empirical Software Engineering. 5: 313-330. DOI: 10.1023/A:1009896203228  0.444
1999 Khoshgoftaar TM, Allen EB. Logistic regression modeling of software quality International Journal of Reliability, Quality and Safety Engineering. 6: 303-317. DOI: 10.1142/S0218539399000292  0.364
1999 KHOSHGOFTAAR TM, ALLEN EB, JONES WD, HUDEPOHL JP. DATA MINING FOR PREDICTORS OF SOFTWARE QUALITY International Journal of Software Engineering and Knowledge Engineering. 9: 547-563. DOI: 10.1142/S0218194099000309  0.455
1999 KHOSHGOFTAAR TM, ALLEN EB, NAIK A, JONES WD, HUDEPOHL JP. USING CLASSIFICATION TREES FOR SOFTWARE QUALITY MODELS: LESSONS LEARNED International Journal of Software Engineering and Knowledge Engineering. 9: 217-231. DOI: 10.1142/S0218194099000140  0.363
1999 Khoshgoftaar TM, Allen EB. Comparative study of ordering and classification of fault-prone software modules Empirical Software Engineering. 4: 159-186. DOI: 10.1023/A:1009876418873  0.429
1999 Khoshgoftaar TM, Allen EB. Impact of costs of misclassification on software quality modeling Computer Standards & Interfaces. 21: 164-165. DOI: 10.1016/S0920-5489(99)92173-6  0.34
1998 Khoshgoftaar TM. An information theoretic approach to predicting software faults International Journal of Reliability, Quality and Safety Engineering. 5: 227-248. DOI: 10.1142/S0218539398000224  0.417
1998 Khoshgoftaar TM, Allen EB, Halstead R, Trio GP, Flass RM. Using process history to predict software quality Ieee Computer. 31: 66-72. DOI: 10.1109/2.666844  0.39
1998 Khoshgoftaar TM, Allen EB. Classification of fault-prone software modules: prior probabilities, costs, and model evaluation Empirical Software Engineering. 3: 275-298. DOI: 10.1023/A:1009736205722  0.467
1997 Khoshgoftaar TM, Allen EB, Lanning DL. An information theory-based approach to quantifying the contribution of a software metric Journal of Systems and Software. 36: 103-112. DOI: 10.1016/0164-1212(95)00063-1  0.405
1996 Lanning DL, Khoshgoftaar TM, Guasti PJ. Improving neural network models of defect content in complex software systems Proceedings of Spie. 2760: 713-724. DOI: 10.1117/12.235963  0.367
1996 Khoshgoftaar TM, Szabo RM. Using neural networks to predict software faults during testing Ieee Transactions On Reliability. 45: 456-462. DOI: 10.1109/24.537016  0.391
1996 Khoshgoftaar TM. Analysis and differentiation of software system environments Software Quality Journal. 5: 127-139. DOI: 10.1007/Bf00419776  0.369
1995 Khoshgoftaar TM, Szabo RM, Guasti PJ. Exploring the behaviour of neural network software quality models Software Engineering Journal. 10: 89. DOI: 10.1049/Sej.1995.0012  0.406
1995 Khoshgoftaar TM, Pandya AS, Lanning DL. Application of neural networks for predicting program faults Annals of Software Engineering. 1: 141-154. DOI: 10.1007/Bf02249049  0.421
1995 Khoshgoftaar TM, Szabo RM. Investigating ARIMA models of software system quality Software Quality Journal. 4: 33-48. DOI: 10.1007/Bf00404648  0.428
1994 KHOSHGOFTAAR TM, SZABO RM. PREDICTING SOFTWARE QUALITY, DURING TESTING, USING NEURAL NETWORK MODELS: A COMPARATIVE STUDY International Journal of Reliability, Quality and Safety Engineering. 1: 303-319. DOI: 10.1142/S0218539394000222  0.416
1994 Khoshgoftaar TM, Lanning DL, Pandya AS. A Comparative Study of Pattern Recognition Techniques for Quality Evaluation of Telecommunications Software Ieee Journal On Selected Areas in Communications. 12: 279-291. DOI: 10.1109/49.272878  0.373
1994 Huynh KD, Khoshgoftaar TM. A performance analysis of advanced I/O architectures for PC-based network file servers Distributed Systems Engineering. 1: 332-344. DOI: 10.1088/0967-1846/1/6/002  0.313
1994 Khoshgoftaar TM, Szabo RM, Woodcock TG. An empirical study of program quality during testing and maintenance Software Quality Journal. 3: 137-151. DOI: 10.1007/Bf00402294  0.394
1994 Khoshgoftaar TM, Allen EB. Applications of information theory to software engineering measurement Software Quality Journal. 3: 79-103. DOI: 10.1007/Bf00213632  0.354
1993 Huynh K, Khoshgoftaar T, Marazas G. A high-level performance analysis of the IBM subsystem control block (SCB) architecture Microprocessing and Microprogramming. 36: 109-125. DOI: 10.1016/0165-6074(93)90252-G  0.335
1992 Khoshgoftaar TM, Bhattacharyya BB, Richardson GD. Predicting Software Errors, During Development, Using Nonlinear Regression Models: A Comparative Study Ieee Transactions On Reliability. 41: 390-395. DOI: 10.1109/24.159804  0.418
1992 Huynh KD, Fernandez EB, Khoshgoftaar TM. A workload model for frame-based real-time applications on distributed systems The Journal of Systems and Software. 18: 255-271. DOI: 10.1016/0164-1212(92)90102-P  0.349
1992 Khoshgoftaar TM, Munson JC, Ravichandran S. Comparative aspects of software complexity metrics and program modules - a multidimensional scaling approach Software Quality Journal. 1: 159-173. DOI: 10.1007/Bf01720923  0.332
1992 Khoshgoftaar TM, Woodcock TG. Software reliability model selection Quality and Reliability Engineering. 8: 457-469. DOI: 10.1002/Qre.4680080509  0.396
1991 Leu S, Fernandez EB, Khoshgoftaar T. Fault-tolerant software reliability modeling using Petri nets Microelectronics Reliability. 31: 645-667. DOI: 10.1016/0026-2714(91)90008-U  0.351
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