Decision trees using the minimum Entropy-of-error principle

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

Volumn 5702 LNCS, Issue , 2009, Pages 799-807

  De Sá, J P Marques ^a   Gama, João ^b   Sebastião, Raquel ^b   Alexandre, Luís A ^c  

^a INEB INSTITUTO DE ENGENHARIA BIOMÉDICA   (Portugal)

^b UNIVERSITY OF PORTO   (Portugal)

^c UNIVERSITY OF BEIRA INTERIOR   (Portugal)

Author keywords

Decision trees; Entropy of error; Node split criteria

Indexed keywords

BINARY DECISION TREES; CLASS DISTRIBUTIONS; GENERALIZATION PROPERTIES; MINIMUM ENTROPY; NEURAL NETWORK TRAINING; NEW CONCEPT; NODE SPLIT CRITERIA; UNIVARIATE;

BLIND SOURCE SEPARATION; DECISION TREES; ELECTRONIC MEDICAL EQUIPMENT; ENTROPY; IMAGE ANALYSIS; NEURAL NETWORKS;

BINARY TREES;

EID: 70349306674     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03767-2_97     Document Type: Conference Paper

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