Case text classification method, system and storage medium based on naive bayes

Abstract

The invention discloses a case text classification method based on naive Bayes, a system and a storage medium. The method comprises the following steps: a classifier is constructed based on the naiveBayes algorithm; Obtaining training samples to train the classifier; Obtaining text to be categorized; The text vector of the text to be classified is obtained by preprocessing the text to be classified; Inputting the text vector into a classifier, and calculating a posterior probability of the text to be classified belonging to each category according to a priori probability of each category anda priori probability of each feature word belonging to each category; The class with the highest posterior probability is output as the classification result. The invention fully considers the difference of the sample quantity between different categories, and takes the prior probability of each category and the prior probability of each characteristic word belonging to each category as the calculation factor of the classifier, so that the invention has better classification effect on case text classification. The invention can be widely applied in the field of data mining.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a naive Bayesian-based case text classification method, system and storage medium. Background technique [0002] The text classification method is a supervised classification method. It uses a text dataset with a marked category to train the classifier, and then uses the trained classifier to classify the text of the unmarked category. The commonly used classification algorithms are simple Bayesian method, K-nearest neighbor method, support vector machine method, etc. Among them, the naive Bayesian classification method is currently recognized as a simple and effective classification method, and it shows satisfactory performance in the field of text classification. However, the case texts of public security have the characteristics of unbalanced category distribution, that is, the characteristics of the large difference in the number of texts contained in each category of the training ...

AI Technical Summary

Problems solved by technology

However, the case texts of public security have the characteristics of unbalanced category distribution, that is, the characteristics of the large difference in the number of texts contained in each category of the training set, so the present invention proposes an improved Naive Bayesian method to classify case texts

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