On sensitivity of case-based reasoning to optimal feature subsets in business failure prediction

Expert Systems with Applications

Volumn 37, Issue 7, 2010, Pages 4811-4821

  Li, Hui ^a   Huang, Hai Bin ^a   Sun, Jie ^a   Lin, Chuang ^b  

^a ZHEJIANG NORMAL UNIVERSITY   (China)

^b DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Business failure prediction (BFP); Case based reasoning (CBR); Chinese listed company; Feature selection; Filters; k Nearest neighbor; Wrappers

Indexed keywords

BASELINE MODELS; BUSINESS FAILURE PREDICTION; CASE SIMILARITY; CBR; CBR SYSTEMS; CHINESE LISTED COMPANIES; CROSS VALIDATION; DATA NORMALIZATION; EMPIRICAL DATA; EMPIRICAL RESULTS; EUCLIDEAN METRICS; FEATURE SELECTION FILTERS; FEATURE SELECTION METHODS; FEATURE SUBSET; FILTER APPROACH; K-NEAREST NEIGHBORS; LEAVE-ONE-OUT; MACHINE LEARNING TECHNIQUES; MULTIPLE DISCRIMINANT ANALYSIS; NEW MODEL; PREDICTIVE PERFORMANCE; RETRIEVAL PROCESS; STEPWISE METHODS; STOCK EXCHANGE; THREE MODELS; WRAPPER APPROACH;

ANALYSIS OF VARIANCE (ANOVA); CASE BASED REASONING; DISCRIMINANT ANALYSIS; FORECASTING; LEARNING ALGORITHMS; OPTIMIZATION; PLANT SHUTDOWNS; SET THEORY; SOFTWARE ARCHITECTURE; SUPPORT VECTOR MACHINES;

BITS;

EID: 77950188976     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.12.034     Document Type: Article

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