Feature selecting method for pattern classification
A feature selection method and pattern classification technology, applied in the field of pattern recognition
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[0070] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0071] Such as image 3 Shown: the present invention scheme realizes the feature selection of pattern classification by following each steps:
[0072] A. Convert the original data into an N×d matrix, where N is the number of samples and d is the feature dimension;
[0073] B. Given threshold ε or iteration number α, given feature importance threshold θ, where the value range of threshold ε is [0.001, 0.01], the value range of iteration number α is [20, 50], feature importance The value interval of the threshold θ is [0.8, 0.95];
[0074] C. Use the k-means algorithm to initialize the membership matrix U=[μ ij ] c×N And the cluster center m=(m 1 ,m 2 ,...,m c ), where u ij Indicates the degree to which the j-th sample belongs to the i-th class, c is the number of split clusters, where i and j are variables and the value intervals are: [1, c], [1,...
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