Use of Multi-category Proximal SVM for Data Set Reduction

In this paper we describe a method for data set reduction by effective use of Multi-category Proximal Support Vector Machine (MPSVM). By using the Linear MPSVM Formulation in an iterative manner we identify the outliers in the data set and eliminate them. A k-Nearest Neighbor (k-NN) classifier is able to classify points using this reduced data set without significant loss of accuracy. We present experiments on a well known large OCR data set to validate our claims.

• Type: Conference
• Year: 2001
• Where: HIS
• Authors: S. V. N. Vishwanathan, M. Narasimha Murty
• Keywords: Data Set, Data Set Reduction, HIS 2001, HIS 2007, Proximal Support Vector