1 CMSC 671 Fall 2010 Class #24 – Wednesday, November 24.
Introduction to SVMs. SVMs Geometric –Maximizing Margin Kernel Methods –Making nonlinear decision boundaries linear –Efficiently! Capacity –Structural.
1 Support Vector Machines Chapter 18.9. Nov 23rd, 2001Copyright © 2001, 2003, Andrew W. Moore Support Vector Machines Andrew W. Moore Professor School.
1 Support Vector Machines. Why SVM? Very popular machine learning technique –Became popular in the late 90s (Vapnik 1995; 1998) –Invented in the late.
STATISTICAL LEARNING METHODS FOR MICROSTRUCTURES
Support Vector Machines
