Kernel Dimensionality Reduction evaluation on various dimensions of effective subspaces for cancer patient survival analysis

10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010

Volumn , Issue , 2010, Pages 790-793

  Chin, Y S ^a   Wasito, Ito ^b   Mohd Hashim, S Z ^a  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b UNIVERSITY OF INDONESIA   (Indonesia)

Author keywords

Dimension of Effective Subspaces (K); Kernel Dimensionality Reduction (KDR)

Indexed keywords

BEST VALUE; CANCER PATIENTS; CLASSIFICATION PERFORMANCE; CLUSTERING APPLICATIONS; DIMENSION OF EFFECTIVE SUBSPACES (K); DIMENSIONALITY REDUCTION; DNA DATA; GENE CLASSIFICATION; K-MEANS; K-MEANS CLUSTERING TECHNIQUES; NEW MODEL; PROPORTIONAL HAZARDS; RANK TEST; REGRESSION MODEL; SEMI-SUPERVISED LEARNING; SURVIVAL ANALYSIS;

BIOINFORMATICS; CLUSTER ANALYSIS; GENES; REGRESSION ANALYSIS; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES;

VECTORS;

EID: 78650267244     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISSPA.2010.5605512     Document Type: Conference Paper

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