Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning
Vojislav Kecman, University of Auckland;
Te-Ming Huang, The University of Auckland;
Ivica Kopriva
Springer International Publishing, 2006
ISBN: 3-540-31681-7;
Language: English
Written for engineers and scientists, this book provides an introduction to the theory and algorithms for mining huge data sets. Topics covered include manifold approaches, component analysis, and low density separation.
MATLAB is introduced and used to solve some examples in the book. In addition, a companion set of MATLAB M-files is available for download.
