Duration: December 2011 to November 2012
University: Indian Institute of Technology, Guwahati
Guide: Dr. V. Vijaya Saradhi
Project Description
One-vs-One, One-vs-All, and Error correcting output codes (ECOC) are some of the most widely employed methods for multi-class classification using binary classifiers. The superiority of any one method over the others has been the subject of much research. In this project, we compare these methods on the basis of parameters that describe an optimal separating hyperplane in the best possible way, namely the training error, the S-span, the fraction of support vectors and the margin of individual hyperplanes unlike the traditional method of comparing them along the test error. We proposed a novel method of using Data Envelopment Analysis (DEA) to compute the relative efficiencies of the hyperplanes instead of comparing the entire ensemble as one.