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A device damage feature screening method based on information entropy and person correlation coefficient

The present application belongs to the field of feature extraction in machine learning, in particular to a device damage feature screening method based on information entropy and Person correlation coefficient. First, according to the principle of power law, the method of fuzzy mutual information is used to select strong correlation features, in order to reduce redundancy, by referring to matrix transformation, the Person correlation coefficient is used to calculate the correlation between strong correlation features, and the redundant features with strong correlation are removed, finally, in order to improve the complementarity, whether there is strong correlation based on combination in the remaining other features is considered by using joint adjustment mutual information calculation. Compared with the prior art, the present application not only considers the correlation between features, but also reduces the redundancy between features, and also considers the complementarity between features from the joint feature angle, thereby maximizing the accuracy of feature selection and improving the efficiency of machine learning method.
Owner:ARMY ENG UNIV OF PLA