An Improved Naive Bayes Classifier for Large Scale Text
Huaixin Chen, Daocai Fu · 2018
Naïve Bayes classifiers is widely used for text classification because of its simplicity and effectiveness.In this paper, an improved Naïve Bayes classifiers was proposed, using multinomial model to modify its rough parameter estimation and parallel competing with MapReduce to categories to text documents.The experimental results show that the proposed method is able to improve the accuracy of Naïve Bayes classifiers dramatically, and has good scalability and extensibility for large-scale text classification.