A divide-and-conquer recursive approach for scaling up instance selection algorithms

Data Mining and Knowledge Discovery

Volumn 18, Issue 3, 2009, Pages 392-418

  De Haro García, Aida ^a   García Pedrajas, Nicolás ^a  

^a UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Divide and conquer; Instance based learning; Instance selection; Scalability

Indexed keywords

DATA-SETS; DIVIDE-AND-CONQUER; EXECUTION TIME; FAST EXECUTION TIME; INSTANCE BASED LEARNING; INSTANCE SELECTION; INSTANCE SELECTION FOR INSTANCE-BASED LEARNING; LARGE DATA SETS; RECURSIVE APPROACHES; SCALING PROBLEMS; SCALING-UP; STANDARD ALGORITHMS; TRAINING SETS; UCI MACHINE LEARNING REPOSITORIES;

EDUCATION; LEARNING SYSTEMS; PHILOSOPHICAL ASPECTS; RECURSIVE FUNCTIONS; SCALABILITY;

ALGORITHMS;

EID: 65049087517     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-008-0121-2     Document Type: Article

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