About this document

SVM Kernel Functions and Estimation Techniques by Uday Gulghane is a document available to read on EtoBox.

This document contains solutions to problems from Problem Set 3 of the 6.867 Machine Learning course. It includes proofs that various combinations of kernel functions result in valid kernel functions that can be used for support vector machines. It also includes MATLAB code for building an SVM from training data using a specified kernel function, computing the discriminant function for new data, and running an experiment to test an SVM on training and test data for one kernel function.

Author

Uday Gulghane

Language

EN