Support Vector Machines Illuminated

View Sample PDF

Author(s): David R. Musicant (Carleton College, USA)
Copyright: 2005
Pages: 6
Source title: Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch201

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

Purchase

View Support Vector Machines Illuminated on the publisher's website for pricing and purchasing information.

Abstract

In recent years, massive quantities of business and research data have been collected and stored, partly due to the plummeting cost of data storage. Much interest has therefore arisen in how to mine this data to provide useful information. Data mining as a discipline shares much in common with machine learning and statistics, as all of these endeavors aim to make predictions about data as well as to better understand the patterns that can be found in a particular dataset. The support vector machine (SVM) is a current machine learning technique that performs quite well in solving common data mining problems.

The IRMA Community

Research IRM

Support Vector Machines Illuminated

Purchase

Abstract

Related Content

IRMA Sponsors