Research on Text Combination Classifier Based on KNN and Bayesian Algorithm
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Text classification is the basis of data mining, which can provide an important guarantee for us to effectively and accurately mine valuable information from a large number of text information, so how to quickly and accurately classify a large number of text is a key problem in data mining. Based on the research of text classification algorithms, this paper designs a combined classifier based on KNN and naive Bayes for the features and feature extraction methods of Chinese text dataset, which effectively improves the accuracy of feature vectors and the accuracy of classification methods, and makes up for the shortcomings of existing text classification methods. The experimental results show that the recall and precision of the text classification system based on the combined model are significantly improved.
KNN, Bayes, Text classification, classifier