Accuracy, parsimony, and generality in evolutionary learning systems via multiobjective selection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2661, Issue , 2003, Pages 118-142

  Llorà, Xavier ^a   Goldberg, David E ^a   Traus, Ivan ^b   Bernadó, Ester ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b UNIVERSITAT RAMON LLULL   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTATIONAL COMPLEXITY; ERROR ANALYSIS; PERTURBATION TECHNIQUES; QUALITY ASSURANCE; SPURIOUS SIGNAL NOISE;

EVOLUTIONARY LEARNING; HIGH QUALITY; IMPACT OF NOISE; LEARNING CLASSIFIER SYSTEM; LEARNING PROCESS; MULTIOBJECTIVE APPROACH; MULTIOBJECTIVE SELECTIONS; TARGET CONCEPT; EVOLUTIONARY LEARNING SYSTEMS; PARETO FRONT; PITTSBURGH LEARNING CLASSIFIER SYSTEMS; QUALITY GENERALIZATION HYPOTHESES;

LEARNING SYSTEMS;

EID: 0346325833     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-40029-5_8     Document Type: Conference Paper

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