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.