Hybrid wrapper-filter approaches for input feature selection using maximum relevance and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA)

Proceedings - 2010 4th International Conference on Network and System Security, NSS 2010

Volumn , Issue , 2010, Pages 442-449

  Huda, Shamsul ^a   Yearwood, John ^a   Strainieri, Andrew ^a  

^a UNIVERSITY OF BALLARAT   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BENCH MARKS; DATA MINING APPLICATIONS; DATA SETS; FEATURE RANKING; FEATURE SELECTION; FEATURE SELECTION ALGORITHM; FEATURE SETS; FEATURE SUBSET; FILTER APPROACH; FILTER METHOD; INPUT FEATURES; MACHINE-LEARNING; MUTUAL INFORMATIONS; RESEARCH PROBLEMS; SEARCH PROCESS; SPEED-UPS; WRAPPER APPROACH; WRAPPER-BASED APPROACH;

FEATURE EXTRACTION; FILTRATION; GAIN MEASUREMENT; HEURISTIC METHODS; NETWORK SECURITY;

NEURAL NETWORKS;

EID: 78650399614     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NSS.2010.7     Document Type: Conference Paper

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