The optimized support vector machine with correlative features for classification of natural spearmint essence

International Journal of Innovative Computing, Information and Control

Volumn 6, Issue 3, 2010, Pages 1089-1099

  Song, Xiaofeng ^a   Halgamuge, Saman K ^b   Chen, Dezhao ^c   Hu, Shangxu ^c   Jiang, Bin ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b UNIVERSITY OF MELBOURNE   (Australia)

^c ZHEJIANG UNIVERSITY   (China)

Author keywords

Complex chemical patterns; Correlative component analysis; Eugenic genetic algorithms; Pattern recognition; Support vector machine

Indexed keywords

CHEMICAL PATTERN; CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; COMPONENT ANALYSIS; CORRELATIVE COMPONENT ANALYSIS; EUGENIC GENETIC ALGORITHMS; KERNEL FUNCTION; MULTICOLLINEARITY; MULTIVARIABLE ANALYSIS; ORIGINAL SAMPLE; PENALTY FACTOR;

CHEMICAL ANALYSIS; GENETIC ALGORITHMS; NEURAL NETWORKS; OPTIMIZATION; PATTERN RECOGNITION; REGRESSION ANALYSIS; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 77950100995     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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