期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：2
页码：31-40
DOI：10.14257/ijhit.2015.8.2.03
出版社：SERSC
摘要：Handwritten digit recognition is a task of great importance in many applications. There are different challenges faced while attempting to solve this problem. It has drawn much attention from the field of machine learning and pattern recognition. Minimax probability machine (MPM) is a novel method in machine learning and data mining. In this paper, we present an extension algorithm for MPM, which is named twin minimax probability machine (TWMPM). TWMPM generates two hyperplanes to improve the classification accuracy. Experiment results on several data sets from the UCI repository demonstrate that TWMPM can improve performance of MPM in most cases. The proposed method is used for recognizing the handwritten digits provided in the MNIST data set of images of handwritten digits (0-9). The testing accuracies are improved comparing with MPM.
关键词：Handwritten Digit Recognition ; ; ; Minimax Probability Machine ; ; ; Two ; Hyperplanes
