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Feature weighting filter method based on correlation and Naive Bayes classification method

A Bayesian classification and feature weighting technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problem of sacrificing the computational complexity and simplicity of the model

Inactive Publication Date: 2017-02-08
CHINA UNIV OF GEOSCIENCES (WUHAN)
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AI Technical Summary

Problems solved by technology

The remaining methods, although taking into account both the correlation between feature variables and class variables and the redundancy between feature variables and feature variables, all sacrifice the computational complexity and simplicity of the model

Method used

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  • Feature weighting filter method based on correlation and Naive Bayes classification method
  • Feature weighting filter method based on correlation and Naive Bayes classification method
  • Feature weighting filter method based on correlation and Naive Bayes classification method

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with embodiment.

[0036] The invention provides a feature weighted filtering method based on correlation, comprising the following steps:

[0037] (1) Suppose A 1 ,A 2 ,...,A m Represents m feature variables of a known training instance set, a i Represents the characteristic variable A i The value of i∈[1,m]; C represents the class variable of the training instance, c represents the value of C, then for each feature variable A i , use the following formula to calculate the mutual information I(A i ;C):

[0038] I ( A i ; C ) = Σ a i Σ c P ( a i , c ) log P ( a ...

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Abstract

The present invention provides a feature weighting filter method based on correlation and a Naive Bayes classification method. The weight value of each feature variable is directly defined as the difference of the correlation of the feature variable and the class variable and the average redundancy of the feature variable and other feature variables. The present invention also provides a feature weighting Naive Bayes classification method depending on the method mentioned above. One group of obtained weighting values is substituted into the Naive Bayes classification formula for final classification of the test example. The feature weighting filter method based on correlation and the Naive Bayes classification method consider the correlation of the feature variable and the class variable and the redundancy between feature variables and maintain the model calculation complexity and the simplicity so as to verify the validity and the accuracy of the feature weighting method and the classification method provided by the invention through lots of experiment researches.

Description

technical field [0001] The invention relates to a correlation-based feature weighted filtering method and a naive Bayesian classification method, belonging to the technical field of artificial intelligence data mining classification. Background technique [0002] Suppose A 1 , A 2 ,...,A m are m feature variables, and a test instance x can be expressed as a feature vector<a 1 , a 2 ,...,a m >, where a i is the feature variable A i value of . Let C denote the class variable, c denote the value of C, and feature-weighted Naive Bayes uses Equation 1 to classify x. [0003] c ( x ) = arg max c ∈ C P ( c ) Π i = 1 m P ( a i | c ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/24155
Inventor 蒋良孝张伦干李超群
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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