Threshold accepting trained principal component neural network and feature subset selection: Application to bankruptcy prediction in banks

Applied Soft Computing Journal

Volumn 8, Issue 4, 2008, Pages 1539-1548

  Ravi, V ^a   Pramodh, C ^a  

^a INSTITUTE FOR DEVELOPMENT AND RESEARCH IN BANKING TECHNOLOGY   (India)

Author keywords

Bankruptcy prediction; Feature subset selection; Generalization; Pattern classification; Principal component analysis; Principal component neural networks; ROC curve; Threshold accepting

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; FINANCIAL DATA PROCESSING; FORECASTING; HEURISTIC ALGORITHMS; HEURISTIC METHODS; HEURISTIC PROGRAMMING; IMAGE CLASSIFICATION; LEARNING SYSTEMS; NEURAL NETWORKS;

10-FOLD CROSS-VALIDATION; BANKRUPTCY PREDICTION; BANKRUPTCY PREDICTIONS; COMMERCIAL BANKS; DATA SETS; DISCRIMINATING POWER; FEATURE SUBSET SELECTION; FEATURE SUBSETS; GENERALIZATION; HIDDEN LAYERS; HIDDEN NODES; INPUT LAYERS; PATTERN CLASSIFICATION; PRE PROCESSORS; PRINCIPAL COMPONENT NEURAL NETWORK; PRINCIPAL COMPONENT NEURAL NETWORKS; PRINCIPAL COMPONENTS; RECEIVER OPERATING CHARACTERISTIC CURVES; ROC CURVE; ROC CURVES; SPANISH; THRESHOLD ACCEPTING; TURKISH;

PRINCIPAL COMPONENT ANALYSIS;

EID: 50149113096     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2007.12.003     Document Type: Article

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