发明名称 LEARNING METHOD FOR BINARY CLASSIFIER CLASSIFYING SAMPLE INTO FIRST CLASS AND SECOND CLASS
摘要 PROBLEM TO BE SOLVED: To provide a binary classification method based on a hyperplane discriminant for simplifying an optimization task. SOLUTION: A set of training samples is acquired, and the respective training samples are labeled to be classified to either of first or second class. A pair of binary samples are connected together by a projective vector so that a first sample of each binary pair belongs to a first class and a second sample of each binary pair belongs to the second class. A set of the hyperplanes is formed so that the set of the hyperoplanes is provided with a plane orthogonal to the projective vector, and one hyperplane minimizing a weighted classification error is selected from the set of the hyperplanes. The set of the training samples is weighted according to the classification based on the selected hyperplane. The selected hyperplanes are connected together and turned into a binary classifier, and when selection and weighting are repeated predetermined times, a final classifier classifying a test sample into the first and second classes is obtained. COPYRIGHT: (C)2004,JPO
申请公布号 JP2004127238(A) 申请公布日期 2004.04.22
申请号 JP20030108519 申请日期 2003.04.14
申请人 MITSUBISHI ELECTRIC RESEARCH LABORATORIES INC 发明人 MOGHADDAM BABACK
分类号 G06N3/00;G06K9/62;G06T7/00;(IPC1-7):G06N3/00 主分类号 G06N3/00
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