Support Vector Machines: Hype or Hallelujah?

Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. The goal of this tutorial is to provide an intuitive explanation of SVMs from a geometric perspective. The classification problem is used to investigate the basic concepts behind SVMs and to examine their strengths and weaknesses from a data mining perspective. While this overview is not comprehensive, it does provide resources for those interested in further exploring SVMs. Keywords Support Vector Machines, Kernel Methods, Statistical Learning Theory.

• Type: Journal
• Year: 2000
• Where: SIGKDD
• Authors: Kristin P. Bennett, Colin Campbell
• Keywords: Data Mining Perspective, Kernel Methods, SIGKDD 2000, Support Vector Machines