Support Vector Machine & Its Applications
SVM Support Vector Machines Presented by: Anas Assiri Supervisor Prof. Dr. Mohamed Batouche.
Introduction to SVMs. SVMs Geometric –Maximizing Margin Kernel Methods –Making nonlinear decision boundaries linear –Efficiently! Capacity –Structural.
STATISTICAL LEARNING METHODS FOR MICROSTRUCTURES
