Chinese text classification has been in the research stage, there are many machine learning algorithms that can be used, such as logical regression, SVM, KNN, naive Bayes, random forest, neural network and so on. In this paper, taking Chinese modern novels as an example, we use various algorithms for classification and comparison, and choose the best algorithm for naive Bayes and neural network. After adjusting the TF-IDF algorithm and processing the participle according to the TF-IDF value, the accuracy of classification is improved obviously. The logistic regression with the lowest accuracy can increase about 6.7%,while the simple Bias and neural network can reach 100%.
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