A new feature selection method based on stability theory - Exploring parameters space to evaluate classification accuracy in neuroimaging data

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

Volumn 7263 LNAI, Issue , 2012, Pages 51-59

  Rondina, Jane M ^a,b   Shawe Taylor, John ^b   Mourão Miranda, Janaina ^a,b  

^a KING'S COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ACCURACY; DATA SETS; FALSE POSITIVE; FEATURE SELECTION METHODS; GRID SEARCH; LOW RATES; STABILITY THEORIES;

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; NEUROIMAGING;

DATA PROCESSING;

EID: 84870034166     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-34713-9_7     Document Type: Conference Paper

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