An Exploration on Text Classification with Classical Machine Learning Algorithm
Yuhan Zheng · 2019
Text classification is an essential part of the NLP, which aims to predict the categories for given texts in a particular classification system. There are many ways of feature selection and classification models. However, most researchers would like to use the encapsulated methods of third-party libraries to achieve their goals. Therefore, in this paper, we propose to implement code to achieve functions, instead of using third-party libraries. We evaluate our code in different classification models, and the result of our experiment shows that our code is feasible.