Studies in Computational Intelligence
1 primary work • 2 total works
Book 17
Kernel Based Algorithms for Mining Huge Data Sets
by Te-Ming Huang, Vojislav Kecman, and Ivica Kopriva
This is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction and shows the similarities and differences between the two most popular unsupervised techniques.
