Identifying learners robust to low quality data

Informatica (Ljubljana)

Volumn 33, Issue 3, 2009, Pages 245-259

  Folleco, Andres A ^a   Khoshgoftaar, Taghi M ^a   Van Hulse, Jason ^a   Napolitano, Amri ^a  

^a FLORIDA ATLANTIC UNIVERSITY   (United States)

Author keywords

Class imbalance; Quality of data; Random forest; Robust learning

Indexed keywords

CLASS DISTRIBUTIONS; CLASS IMBALANCE; CLASSIFICATION ALGORITHM; CLASSIFICATION MODELS; CLASSIFICATION PERFORMANCE; DATA SETS; ENSEMBLE LEARNING; IMBALANCED DATA; INDEPENDENT VARIABLES; LEARNING TECHNIQUES; LOW QUALITIES; MEASUREMENT DATA; NEGATIVE IMPACTS; NOISY DATA; PERFORMANCE METRICS; QUALITY OF DATA; RANDOM FOREST; RANDOM FORESTS; REAL WORLD ENVIRONMENTS; ROBUST LEARNING; ROBUST PERFORMANCE; SOFTWARE MEASUREMENT; SOFTWARE MEASUREMENT DATA;

COMPUTER SOFTWARE; EDUCATION; ELECTRIC MEASURING INSTRUMENTS; LEARNING ALGORITHMS; REGRESSION ANALYSIS;

DATA MINING;

EID: 70350142137     PISSN: 03505596     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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