An empirical investigation of filter attribute selection techniques for software quality classification

2009 IEEE International Conference on Information Reuse and Integration, IRI 2009

Volumn , Issue , 2009, Pages 272-277

  Gao, Kehan ^a   Khoshgoftaar, Taghi M ^b   Wang, Huanjing ^c  

^a EASTERN CONNECTICUT STATE UNIVERSITY   (United States)

^b FLORIDA ATLANTIC UNIVERSITY   (United States)

^c WESTERN KENTUCKY UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATTRIBUTE SELECTION; CLASSIFICATION MODELS; CLASSIFICATION PERFORMANCE; DATA MINING PROBLEMS; DATA PREPROCESSING; DATA SETS; EMPIRICAL INVESTIGATION; EMPIRICAL RESULTS; FAULT-DETECTION PROCESS; HYBRID SEARCH; KOLMOGOROV-SMIRNOV; MAINTENANCE COST; MODEL CALIBRATION; MODEL EVALUATION; MODEL VALIDATION; PREDICTION ACCURACY; PROBABILISTIC SEARCH; REDUNDANT FEATURES; ROUGH SET; SOFTWARE DEVELOPMENT EFFORT; SOFTWARE DEVELOPMENT PROCESS; SOFTWARE QUALITY; SOFTWARE QUALITY MODELING; SOFTWARE QUALITY MODELS; SOFTWARE SYSTEMS;

COMPUTATIONAL COMPLEXITY; COMPUTER SOFTWARE MAINTENANCE; COST REDUCTION; FAULT DETECTION; INFORMATION USE; SET THEORY; SOFTWARE DESIGN;

COMPUTER SOFTWARE SELECTION AND EVALUATION;

EID: 70449387097     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IRI.2009.5211564     Document Type: Conference Paper

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