Classification and Prediction of English News Text Based on Machine Learning

With the emergence of news media and the continuous development of new technologies such as the Internet, the Internet of Things and 5G, in modern society, people can sit at home and know what is happening at home and abroad through news media and other means. Some people even watch English news directly. In order to help these people better read and understand the categories of English news they are reading; this paper proposes a machine learning based English news text classification and prediction method. Firstly, prepare the English news sample data (20Newgroups dataset); The second step is to preliminarily initialize and analyze the dataset; Then comes the modeling stage, which includes several small steps such as dataset splitting, TF-IDF analysis and processing, model training (training set score 0.951932, test set score 0.881306), and test set prediction, in order to achieve data mining; The final step is classification prediction, using the model to predict actual new data and verify the model’s generalization level. After a series of operational evaluations, the model performs well, responds quickly, and has strong stability, which can meet the research requirements of this article.