Evaluating switching neural networks through artificial and real gene expression data

Artificial Intelligence in Medicine

Volumn 45, Issue 2-3, 2009, Pages 163-171

  Muselli, Marco ^a   Costacurta, Massimiliano ^a   Ruffino, Francesca ^b  

^a CNR   (Italy)

^b UNIVERSITY OF MILAN   (Italy)

Author keywords

Gene selection; Machine learning; Recursive feature addition; Shadow clustering; Switching neural networks

Indexed keywords

GENE SELECTION; MACHINE LEARNING; RECURSIVE FEATURE ADDITION; SHADOW CLUSTERING; SWITCHING NEURAL NETWORKS;

BIOACTIVITY; BIOASSAY; BIOCHIPS; CLUSTER ANALYSIS; COMPUTER SIMULATION; GENE EXPRESSION; MATHEMATICAL MODELS; NUCLEIC ACIDS; QUALITY CONTROL; RECURSIVE FUNCTIONS; ROBOT LEARNING; SIGNAL TO NOISE RATIO; SUPPORT VECTOR MACHINES; SWITCHING;

NEURAL NETWORKS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; GENE SELECTION; GENETIC ANALYSIS; HUMAN; MATHEMATICAL MODEL; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; RECURSIVE FEATURE ADDITION; RELIABILITY; SIGNAL NOISE RATIO; SUPPORT VECTOR MACHINE; SWITCHING NEURAL NETWORK; TECHNIQUE;

GENE EXPRESSION; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER);

EID: 61449090610     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2008.08.002     Document Type: Article

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