Use of Multi-category Proximal SVM for Data Set Reduction
نویسندگان
چکیده
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.
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