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Taghi M. Khoshgoftaar: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Wendell D. Jones, John P. Hudepohl, Taghi M. Khoshgoftaar, Edward B. Allen
    Application of a Usage Profile in Software Quality Models. [Citation Graph (0, 0)][DBLP]
    CSMR, 1999, pp:148-159 [Conf]
  2. Matthew P. Evett, Taghi M. Khoshgoftaar, Pei-der Chien, Edward B. Allen
    Using Genetic Programming to Determine Software Quality. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 1999, pp:113-117 [Conf]
  3. Matthew P. Evett, Taghi M. Khoshgoftaar, Pei-der Chien, Edward B. Allen
    Modelling software quality with GP. [Citation Graph (0, 0)][DBLP]
    GECCO, 1999, pp:1232- [Conf]
  4. Yi Liu, Taghi M. Khoshgoftaar
    Building Decision Tree Software Quality Classification Models Using Genetic Programming. [Citation Graph (0, 0)][DBLP]
    GECCO, 2003, pp:1808-1809 [Conf]
  5. Taghi M. Khoshgoftaar, Mohamed E. Abushadi
    Resource-Sensitive Intrusion Detection Models for Network Traffic. [Citation Graph (0, 0)][DBLP]
    HASE, 2004, pp:249-258 [Conf]
  6. Taghi M. Khoshgoftaar, Edward B. Allen
    Predicting Fault-Prone Software Modules in Embedded Systems with Classification Trees. [Citation Graph (0, 0)][DBLP]
    HASE, 1999, pp:105-0 [Conf]
  7. Taghi M. Khoshgoftaar, Edward B. Allen, Lofton A. Bullard, Robert Halstead, Gary P. Trio
    A tree-based classification model for analysis of a military software system. [Citation Graph (0, 0)][DBLP]
    HASE, 1996, pp:244-0 [Conf]
  8. Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, Gary P. Trio, Ronald M. Flass
    Process Measures for Predicting Software Quality. [Citation Graph (0, 0)][DBLP]
    HASE, 1997, pp:155-0 [Conf]
  9. Taghi M. Khoshgoftaar, Edward B. Allen, Archana Naik, Wendell D. Jones, John P. Hudepohl
    Using Classification Trees for Software Quality Models: Lessons Learned. [Citation Graph (0, 0)][DBLP]
    HASE, 1998, pp:82-89 [Conf]
  10. Taghi M. Khoshgoftaar, Erik Geleyn, Laurent A. Nguyen, Lofton A. Bullard
    Cost-Sensitive Boosting In Software Quality Modeling. [Citation Graph (0, 0)][DBLP]
    HASE, 2002, pp:51-62 [Conf]
  11. Yi Liu, Taghi M. Khoshgoftaar
    Genetic Programming Model for Software Quality Classification. [Citation Graph (0, 0)][DBLP]
    HASE, 2001, pp:127-0 [Conf]
  12. Yi Liu, Taghi M. Khoshgoftaar
    Reducing Overfitting in Genetic Programming Models for Software Quality Classification. [Citation Graph (0, 0)][DBLP]
    HASE, 2004, pp:56-65 [Conf]
  13. Donald F. Schenker, Taghi M. Khoshgoftaar
    The Application of Fuzzy Enhanced Case-Based Reasoning for Identifying Fault-Prone Modules. [Citation Graph (0, 0)][DBLP]
    HASE, 1998, pp:90-97 [Conf]
  14. Shi Zhong, Taghi M. Khoshgoftaar, Naeem Seliya
    Unsupervised Learning for Expert-Based Software Quality Estimation. [Citation Graph (0, 0)][DBLP]
    HASE, 2004, pp:149-155 [Conf]
  15. Naeem Seliya, Taghi M. Khoshgoftaar, Shi Zhong
    Analyzing Software Quality with Limited Fault-Proneness Defect Data. [Citation Graph (0, 0)][DBLP]
    HASE, 2005, pp:89-98 [Conf]
  16. Taghi M. Khoshgoftaar, Lofton A. Bullard, Kehan Gao
    Detecting Outliers Using Rule-Based Modeling for Improving CBR-Based Software Quality Classification Models. [Citation Graph (0, 0)][DBLP]
    ICCBR, 2003, pp:216-230 [Conf]
  17. Taghi M. Khoshgoftaar, Edward B. Allen
    Multivariate assessment of complex software systems: a comparative study. [Citation Graph (0, 0)][DBLP]
    ICECCS, 1995, pp:389-396 [Conf]
  18. John C. Munson, Taghi M. Khoshgoftaar
    The Dimensionality of Program Complexity. [Citation Graph (0, 0)][DBLP]
    ICSE, 1989, pp:245-253 [Conf]
  19. David L. Lanning, Taghi M. Khoshgoftaar
    Canonical Modeling of Software Complexity and Fault Correction Activity. [Citation Graph (0, 0)][DBLP]
    ICSM, 1994, pp:374-381 [Conf]
  20. Wendell D. Jones, Taghi M. Khoshgoftaar, John C. Munson, T. Troy Pearse, George E. Stark
    Hitting the Moving Target: Trials and Tribulations of Modeling Quality in Evolving Software Systems. [Citation Graph (0, 0)][DBLP]
    ICSM, 1998, pp:66-67 [Conf]
  21. Taghi M. Khoshgoftaar, Edward B. Allen
    Can a Software Quality Model Hit a Moving Target? [Citation Graph (0, 0)][DBLP]
    ICSM, 1998, pp:68-70 [Conf]
  22. Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, Gary P. Trio
    Detection of Fault-Prone Software Modules During a Spiral Life Cycle. [Citation Graph (0, 0)][DBLP]
    ICSM, 1996, pp:69-76 [Conf]
  23. Taghi M. Khoshgoftaar, Edward B. Allen, Xiaojing Yuan, Wendell D. Jones, John P. Hudepohl
    Experience Paper: Preparing Measurements of Legacy Software for Predicting Operational Faults. [Citation Graph (0, 0)][DBLP]
    ICSM, 1999, pp:359-0 [Conf]
  24. Taghi M. Khoshgoftaar, John C. Munson, David L. Lanning
    A Comparative Study of Predictive Models for Program Changes During System Testing and Maintenance. [Citation Graph (0, 0)][DBLP]
    ICSM, 1993, pp:72-79 [Conf]
  25. Taghi M. Khoshgoftaar, Robert M. Szabo
    Improving Code Churn Predictions During the System Test and Maintenance Phases. [Citation Graph (0, 0)][DBLP]
    ICSM, 1994, pp:58-67 [Conf]
  26. Taghi M. Khoshgoftaar, Robert M. Szabo, Jeffrey M. Voas
    Detecting program modules with low testability. [Citation Graph (0, 0)][DBLP]
    ICSM, 1995, pp:242-250 [Conf]
  27. Taghi M. Khoshgoftaar, Edward B. Allen, Jason C. Busboom
    Modeling software quality: the Software Measurement Analysis and Reliability Toolkit. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2000, pp:54-61 [Conf]
  28. Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya
    Genetic Programming-Based Decision Trees for Software Quality Classification. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2003, pp:374-383 [Conf]
  29. Taghi M. Khoshgoftaar, Laurent A. Nguyen, Kehan Gao, Jayanth Rajeevalochanam
    Application of an Attribute Selection Method to CBR-Based Software Quality Classification. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2003, pp:47-52 [Conf]
  30. Taghi M. Khoshgoftaar, Naeem Seliya
    Software Quality Classification Modeling Using The SPRINT Decision Tree Algorithm. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2002, pp:365-374 [Conf]
  31. Qiming Luo, Taghi M. Khoshgoftaar
    Efficient Image Segmentation by Mean Shift Clustering and MDL-Guided Region Merging. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2004, pp:337-343 [Conf]
  32. Naeem Seliya, Taghi M. Khoshgoftaar, Shi Zhong
    Semi-Supervised Learning for Software Quality Estimation. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2004, pp:183-190 [Conf]
  33. Wei Tang, Taghi M. Khoshgoftaar
    Noise Identification with the k-Means Algorithm. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2004, pp:373-378 [Conf]
  34. Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert
    A Hybrid Approach to Cleansing Software Measurement Data. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2006, pp:713-722 [Conf]
  35. Shi Zhong, Taghi M. Khoshgoftaar, Shyam Varan Nath
    A Clustering Approach to Wireless Network Intrusion Detection. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2005, pp:190-196 [Conf]
  36. Taghi M. Khoshgoftaar, Kehan Gao
    Assessment of a Multi-Strategy Classifier for an Embedded Software System. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2006, pp:651-658 [Conf]
  37. Xiaoyuan Su, Taghi M. Khoshgoftaar
    Collaborative Filtering for Multi-class Data Using Belief Nets Algorithms. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2006, pp:497-504 [Conf]
  38. Xingquan Zhu, Xindong Wu, Taghi M. Khoshgoftaar, Yong Shi
    An Empirical Study of the Noise Impact on Cost-Sensitive Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:1168-1174 [Conf]
  39. Jason Van Hulse, Taghi M. Khoshgoftaar, Chris Seiffert, Lili Zhao
    Noise correction using bayesian multiple imputation. [Citation Graph (0, 0)][DBLP]
    IRI, 2006, pp:478-483 [Conf]
  40. Taghi M. Khoshgoftaar, Andres Folleco, Jason Van Hulse, Lofton A. Bullard
    Software quality imputation in the presence of noisy data. [Citation Graph (0, 0)][DBLP]
    IRI, 2006, pp:484-489 [Conf]
  41. Taghi M. Khoshgoftaar, Jason Van Hulse
    Empirical case studies in attribute noise detection. [Citation Graph (0, 0)][DBLP]
    IRI, 2005, pp:211-216 [Conf]
  42. Taghi M. Khoshgoftaar, Pierre Rebours
    Generating Multiple Noise Elimination Filters with the Ensemble-Partitioning Filter. [Citation Graph (0, 0)][DBLP]
    IRI, 2004, pp:369-375 [Conf]
  43. Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao
    Rule-Based Noise Detection for Software Measurement Data. [Citation Graph (0, 0)][DBLP]
    IRI, 2004, pp:302-307 [Conf]
  44. Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya
    Labeling network event records for intrusion detection in a Wireless LAN. [Citation Graph (0, 0)][DBLP]
    IRI, 2006, pp:200-206 [Conf]
  45. Yi Liu, Taghi M. Khoshgoftaar, Jenq-Foung Yao
    Developing an effective validation strategy for genetic programming models based on multiple datasets. [Citation Graph (0, 0)][DBLP]
    IRI, 2006, pp:232-237 [Conf]
  46. Qiming Luo, Taghi M. Khoshgoftaar, Edgar An
    Hierarchical indexing of ocean survey video by mean shift clustering and MDL principle. [Citation Graph (0, 0)][DBLP]
    IRI, 2005, pp:404-409 [Conf]
  47. Qiming Luo, Taghi M. Khoshgoftaar, Andres Folleco
    Classification of ships in surveillance video. [Citation Graph (0, 0)][DBLP]
    IRI, 2006, pp:432-437 [Conf]
  48. Zhiwei Xu, Kehan Gao, Taghi M. Khoshgoftaar
    Application of fuzzy expert system in test case selection for system regression test. [Citation Graph (0, 0)][DBLP]
    IRI, 2005, pp:120-125 [Conf]
  49. Yudong Xiao, Taghi M. Khoshgoftaar, Naeem Seliya
    The partitioning- and rule-based filter for noise detection. [Citation Graph (0, 0)][DBLP]
    IRI, 2005, pp:205-210 [Conf]
  50. Taghi M. Khoshgoftaar, Kehan Gao, Robert M. Szabo
    An Application of Zero-Inflated Poisson Regression for Software Fault Prediction . [Citation Graph (0, 0)][DBLP]
    ISSRE, 2001, pp:66-73 [Conf]
  51. Taghi M. Khoshgoftaar
    Improving Usefulness of Software Quality Classification Models Based on Boolean Discriminant Functions. [Citation Graph (0, 0)][DBLP]
    ISSRE, 2002, pp:221-230 [Conf]
  52. Taghi M. Khoshgoftaar, Ruqun Shan, Edward B. Allen
    Improving Tree-Based Models of Software Quality with Principal Components Analysis. [Citation Graph (0, 0)][DBLP]
    ISSRE, 2000, pp:198-209 [Conf]
  53. Taghi M. Khoshgoftaar, Vishal Thaker, Edward B. Allen
    Modeling Fault-Prone Modules of Subsystems. [Citation Graph (0, 0)][DBLP]
    ISSRE, 2000, pp:259-269 [Conf]
  54. Edward B. Allen, Taghi M. Khoshgoftaar
    Measuring Coupling and Cohesion: An Information-Theory Approach. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 1999, pp:119-0 [Conf]
  55. Edward B. Allen, Taghi M. Khoshgoftaar, Ye Chen
    Measuring Coupling and Cohesion of Software Modules: An Information-Theory Approach. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2001, pp:124-134 [Conf]
  56. Ali Idri, Alain Abran, Taghi M. Khoshgoftaar
    Estimating Software Project Effort by Analogy Based on Linguistic Values. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2002, pp:21-0 [Conf]
  57. Taghi M. Khoshgoftaar, Edward B. Allen
    The Impact of Costs of Misclassification on Software Quality Modeling. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 1997, pp:54-0 [Conf]
  58. Taghi M. Khoshgoftaar, Edward B. Allen, Jianyu Deng
    Controlling Overfitting in Software Quality Models: Experiments with Regression Trees and Classification. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2001, pp:190-198 [Conf]
  59. Taghi M. Khoshgoftaar, Edward B. Allen, Xiaojing Yuan, Wendell D. Jones, John P. Hudepohl
    Assessing Uncertain Predictions of Software Quality. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 1999, pp:159-0 [Conf]
  60. Taghi M. Khoshgoftaar, Erik Geleyn, Kehan Gao
    An Empirical Study of the Impact of Count Models Predictions on Module-Order Models. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2002, pp:161-172 [Conf]
  61. Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya
    Module-Order Modeling using an Evolutionary Multi-Objective Optimization Approach. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2004, pp:159-169 [Conf]
  62. Taghi M. Khoshgoftaar, Naeem Seliya
    Tree-Based Software Quality Estimation Models For Fault Prediction. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2002, pp:203-0 [Conf]
  63. Taghi M. Khoshgoftaar, Naeem Seliya
    The Necessity of Assuring Quality in Software Measurement Data. [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 2004, pp:119-130 [Conf]
  64. Norman F. Schneidewind, Wendell D. Jones, Taghi M. Khoshgoftaar, Paul W. Oman, George E. Stark
    Can Metrics and Models be Applied Across Multiple Releases or Projects? [Citation Graph (0, 0)][DBLP]
    IEEE METRICS, 1999, pp:324-0 [Conf]
  65. Khoa D. Huynh, Taghi M. Khoshgoftaar
    A Performance Analysis of the IBM Subsystem Control Block Architecture in a Video Conferencing Environment. [Citation Graph (0, 0)][DBLP]
    ACM Multimedia, 1993, pp:321-330 [Conf]
  66. Taghi M. Khoshgoftaar, Erik Geleyn, Laurent A. Nguyen
    Empirical Case Studies of Combining Software Quality Classification Models. [Citation Graph (0, 0)][DBLP]
    QSIC, 2003, pp:40-0 [Conf]
  67. Taghi M. Khoshgoftaar, Vedang H. Joshi
    Noise Elimination with Ensemble-Classifier Filtering: A Case-Study in Software Quality Engineerin. [Citation Graph (0, 0)][DBLP]
    SEKE, 2004, pp:226-231 [Conf]
  68. Taghi M. Khoshgoftaar, Yudong Xiao, Kehan Gao
    Multi-Objective Optimization by CBR GA-Optimizer for Module-Order Modeling. [Citation Graph (0, 0)][DBLP]
    SEKE, 2004, pp:220-225 [Conf]
  69. Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse
    Polishing Noise in Continuous Software Measurement Data. [Citation Graph (0, 0)][DBLP]
    SEKE, 2006, pp:227-231 [Conf]
  70. Taghi M. Khoshgoftaar, Jason Van Hulse
    Multiple Imputation of Software Measurement Data: A Case Study. [Citation Graph (0, 0)][DBLP]
    SEKE, 2006, pp:220-226 [Conf]
  71. Pierre Rebours, Taghi M. Khoshgoftaar
    Quality Problem in Software Measurement Data. [Citation Graph (0, 0)][DBLP]
    Advances in Computers, 2006, v:66, n:, pp:44-79 [Journal]
  72. Taghi M. Khoshgoftaar, Naeem Seliya
    Software quality estimation with case-based reasoning. [Citation Graph (0, 0)][DBLP]
    Advances in Computers, 2004, v:62, n:, pp:250-293 [Journal]
  73. Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, John P. Hudepohl
    Accuracy of software quality models over multiple releases. [Citation Graph (0, 0)][DBLP]
    Ann. Software Eng., 2000, v:9, n:, pp:103-116 [Journal]
  74. Taghi M. Khoshgoftaar, Abhijit S. Pandya, David L. Lanning
    Application of Neural Networks for Predicting Program Faults. [Citation Graph (0, 0)][DBLP]
    Ann. Software Eng., 1995, v:1, n:, pp:141-154 [Journal]
  75. Zhiwei Xu, Taghi M. Khoshgoftaar
    Software Quality Prediction for High-Assurance Network Telecommunications Systems. [Citation Graph (0, 0)][DBLP]
    Comput. J., 2001, v:44, n:6, pp:557-568 [Journal]
  76. Taghi M. Khoshgoftaar, Edward B. Allen, Robert Halstead, Gary P. Trio, Ronald M. Flass
    Using Process History to Predict Software Quality. [Citation Graph (0, 0)][DBLP]
    IEEE Computer, 1998, v:31, n:4, pp:66-72 [Journal]
  77. Taghi M. Khoshgoftaar, Paul W. Oman
    Software Metrics: Charting the Course - Guest Editors' Introduction. [Citation Graph (0, 0)][DBLP]
    IEEE Computer, 1994, v:27, n:9, pp:13-15 [Journal]
  78. David L. Lanning, Taghi M. Khoshgoftaar
    Modeling the Relationship Between Source Code Complexity and Maintenance Difficulty. [Citation Graph (0, 0)][DBLP]
    IEEE Computer, 1994, v:27, n:9, pp:35-40 [Journal]
  79. Khoa D. Huynh, Taghi M. Khoshgoftaar
    A performance analysis of advanced I/O architectures for PC-based network file servers. [Citation Graph (0, 0)][DBLP]
    Distributed Systems Engineering, 1994, v:1, n:6, pp:332-0 [Journal]
  80. Taghi M. Khoshgoftaar, Naeem Seliya
    Fault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2003, v:8, n:3, pp:255-283 [Journal]
  81. Taghi M. Khoshgoftaar, Naeem Seliya
    Analogy-Based Practical Classification Rules for Software Quality Estimation. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2003, v:8, n:4, pp:325-350 [Journal]
  82. Taghi M. Khoshgoftaar, Naeem Seliya
    Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2004, v:9, n:3, pp:229-257 [Journal]
  83. Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao
    Assessment of a New Three-Group Software Quality Classification Technique: An Empirical Case Study. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2005, v:10, n:2, pp:183-218 [Journal]
  84. Taghi M. Khoshgoftaar, Xiaojing Yuan, Edward B. Allen
    Balancing Misclassification Rates in Classification-Tree Models of Software Quality. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2000, v:5, n:4, pp:313-330 [Journal]
  85. Taghi M. Khoshgoftaar, Xiaojing Yuan, Edward B. Allen, Wendell D. Jones, John P. Hudepohl
    Uncertain Classification of Fault-Prone Software Modules. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2002, v:7, n:4, pp:295-295 [Journal]
  86. Taghi M. Khoshgoftaar, Edward B. Allen
    Controlling Overfitting in Classification-Tree Models of Software Quality. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 2001, v:6, n:1, pp:59-79 [Journal]
  87. Taghi M. Khoshgoftaar, Edward B. Allen
    Classification of Fault-Prone Software Modules: Prior Probabilities, Costs, and Model Evaluation. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 1998, v:3, n:3, pp:275-298 [Journal]
  88. Taghi M. Khoshgoftaar, Edward B. Allen
    A Comparative Study of Ordering and Classification of Fault-Prone Software Modules. [Citation Graph (0, 0)][DBLP]
    Empirical Software Engineering, 1999, v:4, n:2, pp:159-186 [Journal]
  89. Shi Zhong, Taghi M. Khoshgoftaar, Naeem Seliya
    Analyzing Software Measurement Data with Clustering Techniques. [Citation Graph (0, 0)][DBLP]
    IEEE Intelligent Systems, 2004, v:19, n:2, pp:20-27 [Journal]
  90. Zhiwei Xu, Taghi M. Khoshgoftaar
    Identification of fuzzy models of software cost estimation. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2004, v:145, n:1, pp:141-163 [Journal]
  91. Taghi M. Khoshgoftaar, Shi Zhong, Vedang H. Joshi
    Enhancing software quality estimation using ensemble-classifier based noise filtering. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2005, v:9, n:1, pp:3-27 [Journal]
  92. Taghi M. Khoshgoftaar, Jason Van Hulse
    Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2005, v:9, n:6, pp:589-602 [Journal]
  93. Taghi M. Khoshgoftaar, Naeem Seliya, Kehan Gao
    Detecting noisy instances with the rule-based classification model. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2005, v:9, n:4, pp:347-364 [Journal]
  94. Taghi M. Khoshgoftaar, Pierre Rebours
    Evaluating noise elimination techniques for software quality estimation. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2005, v:9, n:5, pp:487-508 [Journal]
  95. Taghi M. Khoshgoftaar, Kehan Gao, Nawal H. Ibrahim
    Evaluating indirect and direct classification techniques for network intrusion detection. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2005, v:9, n:3, pp:309-326 [Journal]
  96. Jason Van Hulse, Taghi M. Khoshgoftaar
    Class noise detection using frequent itemsets. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2006, v:10, n:6, pp:487-507 [Journal]
  97. Taghi M. Khoshgoftaar, Jason Van Hulse
    Determining noisy instances relative to attributes of interest. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2006, v:10, n:3, pp:251-268 [Journal]
  98. Taghi M. Khoshgoftaar, Naeem Seliya
    Software Quality Classification Modeling Using the SPRINT Decision Tree Algorithm. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2003, v:12, n:3, pp:207-225 [Journal]
  99. K. Ganesan, Taghi M. Khoshgoftaar, Edward B. Allen
    Verifying Requirements Through Mathematical Modelling and Animation. [Citation Graph (0, 0)][DBLP]
    International Journal of Software Engineering and Knowledge Engineering, 2000, v:10, n:2, pp:139-152 [Journal]
  100. Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, John P. Hudepohl
    Data Mining for Predictors of Software Quality. [Citation Graph (0, 0)][DBLP]
    International Journal of Software Engineering and Knowledge Engineering, 1999, v:9, n:5, pp:547-564 [Journal]
  101. Taghi M. Khoshgoftaar, Edward B. Allen, Archana Naik, Wendell D. Jones, John P. Hudepohl
    Using Classification Trees for Software Quality Models: Lessons Learned. [Citation Graph (0, 0)][DBLP]
    International Journal of Software Engineering and Knowledge Engineering, 1999, v:9, n:2, pp:217-232 [Journal]
  102. Taghi M. Khoshgoftaar, Bojan Cukic, Naeem Seliya
    Predicting Fault-Prone Modules in Embedded Systems Using Analogy-Based Classification Models. [Citation Graph (0, 0)][DBLP]
    International Journal of Software Engineering and Knowledge Engineering, 2002, v:12, n:2, pp:201-221 [Journal]
  103. Taghi M. Khoshgoftaar, Vedang H. Joshi, Naeem Seliya
    Detecting Noisy Instances with the Ensemble Filter: a Study in Software Quality Estimation. [Citation Graph (0, 0)][DBLP]
    International Journal of Software Engineering and Knowledge Engineering, 2006, v:16, n:1, pp:53-76 [Journal]
  104. Zhiwei Xu, Taghi M. Khoshgoftaar, Edward B. Allen
    Application of fuzzy expert systems in assessing operational risk of software. [Citation Graph (0, 0)][DBLP]
    Information & Software Technology, 2003, v:45, n:7, pp:373-388 [Journal]
  105. Taghi M. Khoshgoftaar, John C. Munson
    Predicting Software Development Errors Using Software Complexity Metrics. [Citation Graph (0, 0)][DBLP]
    IEEE Journal on Selected Areas in Communications, 1990, v:8, n:2, pp:253-261 [Journal]
  106. Khoa D. Huynh, Eduardo B. Fernandez, Taghi M. Khoshgoftaar
    A workload model for frame-based real-time applications on distributed systems. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 1992, v:18, n:3, pp:255-271 [Journal]
  107. Taghi M. Khoshgoftaar, Edward B. Allen, David L. Lanning
    An Information Theory-Based Approach to Quantifying the Contribution of a Software Metric. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 1997, v:36, n:2, pp:103-113 [Journal]
  108. Taghi M. Khoshgoftaar, David L. Lanning
    A neural network approach for early detection of program modules having high risk in the maintenance phase. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 1995, v:29, n:1, pp:85-91 [Journal]
  109. Taghi M. Khoshgoftaar, John C. Munson, David L. Lanning
    Alternative approaches for the use of metrics to order programs by complexity. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 1994, v:24, n:3, pp:211-221 [Journal]
  110. Taghi M. Khoshgoftaar, Naeem Seliya, Angela Herzberg
    Resource-oriented software quality classification models. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 2005, v:76, n:2, pp:111-126 [Journal]
  111. John C. Munson, Taghi M. Khoshgoftaar
    Applications of a relative complexity metric for software project management. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 1990, v:12, n:3, pp:283-291 [Journal]
  112. John C. Munson, Taghi M. Khoshgoftaar
    Measurement of data structure complexity. [Citation Graph (0, 0)][DBLP]
    Journal of Systems and Software, 1993, v:20, n:3, pp:217-225 [Journal]
  113. Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Huang
    The pairwise attribute noise detection algorithm. [Citation Graph (0, 0)][DBLP]
    Knowl. Inf. Syst., 2007, v:11, n:2, pp:171-190 [Journal]
  114. Xingquan Zhu, Taghi M. Khoshgoftaar, Ian Davidson, Shichao Zhang
    Editorial: Special issue on mining low-quality data. [Citation Graph (0, 0)][DBLP]
    Knowl. Inf. Syst., 2007, v:11, n:2, pp:131-136 [Journal]
  115. Khoa D. Huynh, Taghi M. Khoshgoftaar
    Performance Analysis of Advanced I/O Architectures for PC-Based Video Servers. [Citation Graph (0, 0)][DBLP]
    Multimedia Syst., 1994, v:2, n:1, pp:36-50 [Journal]
  116. Khoa D. Huynh, Taghi M. Khoshgoftaar
    A Performance Analysis of Personal Computers in a Video Conferencing Environment. [Citation Graph (0, 0)][DBLP]
    Multimedia Syst., 1994, v:2, n:3, pp:103-117 [Journal]
  117. Khoa D. Huynh, Taghi M. Khoshgoftaar
    A Performance Analysis of an Object-Based I/O Architecture in a Video Server Environment. [Citation Graph (0, 0)][DBLP]
    Multimedia Syst., 1995, v:3, n:4, pp:162-177 [Journal]
  118. Khoa D. Huynh, Taghi M. Khoshgoftaar
    Performance Analysis of a Peer-to-Peer I/O Architecture in Video Server Environments. [Citation Graph (0, 0)][DBLP]
    Multimedia Tools Appl., 1995, v:1, n:3, pp:217-244 [Journal]
  119. Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, John P. Hudepohl
    Which Software Modules have Faults which will be Discovered by Customers? [Citation Graph (0, 0)][DBLP]
    Journal of Software Maintenance, 1999, v:11, n:1, pp:1-18 [Journal]
  120. John P. Hudepohl, Stephen J. Aud, Taghi M. Khoshgoftaar, Edward B. Allen, Jean Mayrand
    Emerald: Software Metrics and Models on the Desktop. [Citation Graph (0, 0)][DBLP]
    IEEE Software, 1996, v:13, n:5, pp:56-60 [Journal]
  121. Taghi M. Khoshgoftaar, Edward B. Allen, Kalai Kalaichelvan, Nishith Goel
    Early Quality Prediction: A Case Study in Telecommunications. [Citation Graph (0, 0)][DBLP]
    IEEE Software, 1996, v:13, n:1, pp:65-71 [Journal]
  122. John C. Munson, Taghi M. Khoshgoftaar
    Measuring Dynamic Program Complexity. [Citation Graph (0, 0)][DBLP]
    IEEE Software, 1992, v:9, n:6, pp:48-55 [Journal]
  123. Taghi M. Khoshgoftaar
    Introduction to the Special Issue on Quality Engineering with Computational Intelligence. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2003, v:11, n:2, pp:85-86 [Journal]
  124. Taghi M. Khoshgoftaar, Edward B. Allen
    Empirical Assessment of a Software Metric: The Information Content of Operators. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2001, v:9, n:2, pp:99-112 [Journal]
  125. Taghi M. Khoshgoftaar, Edward B. Allen
    Ordering Fault-Prone Software Modules. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2003, v:11, n:1, pp:19-37 [Journal]
  126. Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, John P. Hudepohl
    Cost-Benefit Analysis of Software Quality Models. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2001, v:9, n:1, pp:9-30 [Journal]
  127. Taghi M. Khoshgoftaar, Edward B. Allen, Wendell D. Jones, John P. Hudepohl
    Data Mining of Software Development Databases. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2001, v:9, n:3, pp:161-176 [Journal]
  128. Taghi M. Khoshgoftaar, Yi Liu, Naeem Seliya
    A multiobjective module-order model for software quality enhancement. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Evolutionary Computation, 2004, v:8, n:6, pp:593-608 [Journal]
  129. Qiming Luo, Taghi M. Khoshgoftaar
    Unsupervised multiscale color image segmentation based on MDL principle. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Image Processing, 2006, v:15, n:9, pp:2755-2761 [Journal]
  130. Taghi M. Khoshgoftaar, John C. Munson, Bibhuti B. Bhattacharya, Gary D. Richardson
    Predictive Modeling Techniques of Software Quality from Software Measures. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Software Eng., 1992, v:18, n:11, pp:979-987 [Journal]
  131. John C. Munson, Taghi M. Khoshgoftaar
    The Detection of Fault-Prone Programs. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Software Eng., 1992, v:18, n:5, pp:423-433 [Journal]
  132. Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliya
    Low-Effort Labeling of Network Events for Intrusion Detection in WLANs. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2007, pp:490-495 [Conf]
  133. Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano
    Experimental perspectives on learning from imbalanced data. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:935-942 [Conf]
  134. 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. [Citation Graph (0, 0)][DBLP]
    IRI, 2007, pp:651-658 [Conf]
  135. Jason Van Hulse, Taghi M. Khoshgoftaar
    Incomplete-Case Nearest Neighbor Imputation in Software Measurement Data. [Citation Graph (0, 0)][DBLP]
    IRI, 2007, pp:630-637 [Conf]
  136. Yi Liu, Taghi M. Khoshgoftaar, Jenq-Foung Yao
    Building a Novel GP-Based Software Quality Classifier Using Multiple Validation Datasets. [Citation Graph (0, 0)][DBLP]
    IRI, 2007, pp:644-650 [Conf]
  137. Qiming Luo, Taghi M. Khoshgoftaar
    An Empirical Study on Estimating Motions in Video Stabilization. [Citation Graph (0, 0)][DBLP]
    IRI, 2007, pp:360-366 [Conf]
  138. Xiaoyuan Su, Taghi M. Khoshgoftaar
    A Progressive Edge-Based Stereo Correspondence Method. [Citation Graph (0, 0)][DBLP]
    ISVC (1), 2007, pp:248-257 [Conf]
  139. Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Andres Folleco
    Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction. [Citation Graph (0, 0)][DBLP]
    ISVC (2), 2007, pp:469-478 [Conf]
  140. Andres Folleco, Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert
    Learning from Software Quality Data with Class Imbalance and Noise. [Citation Graph (0, 0)][DBLP]
    SEKE, 2007, pp:487-0 [Conf]
  141. Taghi M. Khoshgoftaar, Jason Van Hulse, Chris Seiffert, Lili Zhao
    The multiple imputation quantitative noise corrector. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2007, v:11, n:3, pp:245-263 [Journal]
  142. Taghi M. Khoshgoftaar, Pierre Rebours
    Improving Software Quality Prediction by Noise Filtering Techniques. [Citation Graph (0, 0)][DBLP]
    J. Comput. Sci. Technol., 2007, v:22, n:3, pp:387-396 [Journal]
  143. Taghi M. Khoshgoftaar, Naeem Seliya, Nandini Sundaresh
    An empirical study of predicting software faults with case-based reasoning. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2006, v:14, n:2, pp:85-111 [Journal]
  144. Taghi M. Khoshgoftaar, Angela Herzberg, Naeem Seliya
    Resource oriented selection of rule-based classification models: An empirical case study. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2006, v:14, n:4, pp:309-338 [Journal]
  145. Naeem Seliya, Taghi M. Khoshgoftaar
    Software quality estimation with limited fault data: a semi-supervised learning perspective. [Citation Graph (0, 0)][DBLP]
    Software Quality Journal, 2007, v:15, n:3, pp:327-344 [Journal]

  146. Building Useful Models from Imbalanced Data with Sampling and Boosting. [Citation Graph (, )][DBLP]


  147. Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction. [Citation Graph (, )][DBLP]


  148. A Mixture Imputation-Boosted Collaborative Filter. [Citation Graph (, )][DBLP]


  149. VipBoost: A More Accurate Boosting Algorithm. [Citation Graph (, )][DBLP]


  150. An Evaluation of Sampling on Filter-Based Feature Selection Methods. [Citation Graph (, )][DBLP]


  151. Skewed Class Distributions and Mislabeled Examples. [Citation Graph (, )][DBLP]


  152. A Comparative Study of Data Sampling and Cost Sensitive Learning. [Citation Graph (, )][DBLP]


  153. Mining Data from Multiple Software Development Projects. [Citation Graph (, )][DBLP]


  154. Feature Selection with High-Dimensional Imbalanced Data. [Citation Graph (, )][DBLP]


  155. Arbitrarily-Shaped Window Based Stereo Matching using the Go-Light Optimization Algorithm. [Citation Graph (, )][DBLP]


  156. Comparison of Four Performance Metrics for Evaluating Sampling Techniques for Low Quality Class-Imbalanced Data. [Citation Graph (, )][DBLP]


  157. Using evolutionary sampling to mine imbalanced data. [Citation Graph (, )][DBLP]


  158. An application of a rule-based model in software quality classification. [Citation Graph (, )][DBLP]


  159. Learning with limited minority class data. [Citation Graph (, )][DBLP]


  160. A Comparison of Software Fault Imputation Procedures. [Citation Graph (, )][DBLP]


  161. Identifying noise in an attribute of interest. [Citation Graph (, )][DBLP]


  162. Intrusion detection in wireless networks using clustering techniques with expert analysis. [Citation Graph (, )][DBLP]


  163. Feature Selection with Imbalanced Data for Software Defect Prediction. [Citation Graph (, )][DBLP]


  164. Wrapper-Based Feature Ranking for Software Engineering Metrics. [Citation Graph (, )][DBLP]


  165. RUSBoost: Improving classification performance when training data is skewed. [Citation Graph (, )][DBLP]


  166. VoB predictors: Voting on bagging classifications. [Citation Graph (, )][DBLP]


  167. Using Imputation Techniques to Help Learn Accurate Classifiers. [Citation Graph (, )][DBLP]


  168. Resampling or Reweighting: A Comparison of Boosting Implementations. [Citation Graph (, )][DBLP]


  169. Improving Learner Performance with Data Sampling and Boosting. [Citation Graph (, )][DBLP]


  170. Mining Data with Rare Events: A Case Study. [Citation Graph (, )][DBLP]


  171. An Empirical Study of Learning from Imbalanced Data Using Random Forest. [Citation Graph (, )][DBLP]


  172. Addressing Class Imbalance in Non-binary Classification Problems. [Citation Graph (, )][DBLP]


  173. A Study on the Relationships of Classifier Performance Metrics. [Citation Graph (, )][DBLP]


  174. High-Dimensional Software Engineering Data and Feature Selection. [Citation Graph (, )][DBLP]


  175. An Empirical Study on Wrapper-Based Feature Ranking. [Citation Graph (, )][DBLP]


  176. Exploring Software Quality Classification with a Wrapper-Based Feature Ranking Technique. [Citation Graph (, )][DBLP]


  177. Identifying learners robust to low quality data. [Citation Graph (, )][DBLP]


  178. Hybrid sampling for imbalanced data. [Citation Graph (, )][DBLP]


  179. VCI predictors: Voting on classifications from imputed learning sets. [Citation Graph (, )][DBLP]


  180. An Empirical Comparison of Repetitive Undersampling Techniques. [Citation Graph (, )][DBLP]


  181. An Empirical Investigation of Filter Attribute Selection Techniques for Software Quality Classification. [Citation Graph (, )][DBLP]


  182. Aggregating Performance Metrics for Classifier Evaluation. [Citation Graph (, )][DBLP]


  183. Imputation-boosted collaborative filtering using machine learning classifiers. [Citation Graph (, )][DBLP]


  184. Analyzing the Impact of Attribute Noise on Software Quality Classification. [Citation Graph (, )][DBLP]


  185. On the Rarity of Fault-prone Modules in Knowledge-based Software Quality Modeling. [Citation Graph (, )][DBLP]


  186. Toward Model Checking Web Services Over the Web. [Citation Graph (, )][DBLP]


  187. An Extendible Translation of BPEL to a Machine-verifiable Model. [Citation Graph (, )][DBLP]


  188. A Novel Hybrid Search Algorithm for Feature Selection. [Citation Graph (, )][DBLP]


  189. Value-Based Software Quality Modeling. [Citation Graph (, )][DBLP]


  190. Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts. [Citation Graph (, )][DBLP]


  191. Imputed Neighborhood Based Collaborative Filtering. [Citation Graph (, )][DBLP]


  192. A Comparative Study of Threshold-Based Feature Selection Techniques. [Citation Graph (, )][DBLP]


  193. Software quality modeling: The impact of class noise on the random forest classifier. [Citation Graph (, )][DBLP]


  194. Assuring Timeliness in an e-Science Service-Oriented Architecture. [Citation Graph (, )][DBLP]


  195. Knowledge discovery from imbalanced and noisy data. [Citation Graph (, )][DBLP]


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