A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization

Genomics

Volumn 107, Issue 6, 2016, Pages 231-238

  Vafaee Sharbaf, Fatemeh ^a   Mosafer, Sara ^a   Moattar, Mohammad Hossein ^b  

^a IMAM REZA INTERNATIONAL UNIVERSITY   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Ant colony optimization; Cellular learning automata; Gene selection; K nearest neighbor; Microarray data; Na ve Bayes

Indexed keywords

ANALYTIC METHOD; ANT COLONY METHOD; AREA UNDER THE CURVE; ARTICLE; BAYESIAN LEARNING; CELLULAR LEARNING AUTOMATA; DATA ANALYSIS; GENETIC SELECTION; MATHEMATICAL ANALYSIS; MEASUREMENT ACCURACY; MICROARRAY ANALYSIS; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; ALGORITHM; CLUSTER ANALYSIS; DNA MICROARRAY; HUMAN; MACHINE LEARNING; PROCEDURES; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; HUMANS; MACHINE LEARNING; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE;

EID: 84973487381     PISSN: 08887543     EISSN: 10898646     Source Type: Journal    
DOI: 10.1016/j.ygeno.2016.05.001     Document Type: Article

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