Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-Supervised, and Unsupervised Learning

By Te-Ming Huang, Vojislav Kecman, Ivica Kopriva

Book Overview

Support Vector Machines in Classification and Regression - An Introduction.- Iterative Single Data Algorithm for Kernel Machines from Huge Data Sets: Theory and Performance.- Feature Reduction with Support Vector Machines and Application in DNA Microarray Analysis.- Semi-supervised Learning and Applications.- Unsupervised Learning by Principal and Independent Component Analysis.

• Format: Paperback
• Language: English
• ISBN: 3642068561
• ISBN13: 9783642068560
• Release Date: November 2010
• Publisher: Springer
• Length: 260 Pages
• Weight: 0.87 lbs.
• Dimensions: 0.6" x 6.1" x 9.2"