Patent ID: 7958070
Filing Date: 2011-06-07
Classification: G06K

Abstract:
1. A computer-implemented method to optimize parameters for classifying input data into one of a plurality of classes, the method comprising: inputting a plurality of pieces of learning data, each associated with a class to which the piece of the learning data belongs; calculating a statistical amount of attribute values of elements in each of specific k parts, k being equal to or larger than 1, in each piece of the learning data; mapping each piece of the learning data in a k-dimensional feature space as a vector having the calculated k statistical amounts as elements; calculating a first parameter which defines a classification function based on vectors obtained by mapping the learning data; and optimizing a second parameter which defines a boundary value of the classification function to classify the input data into one of the plurality of classes in the k-dimensional feature space by trying to classify the vectors with each of a plurality of candidates for the boundary value and selecting one of the candidates which minimize an error of a class in which the vectors are classified using the candidate against the class to which the learning data corresponding to the vectors belong.