Automated text classification model based on projection pursuit regression

When a text is expressed as a vector space model, it becomes high-dimensional data. Dimensional reduction is a feasible and effective method of analyzing highdimensional data, and projection pursuit technique is a statistical and nonparametric dimensional reduction method in which data does not need to satisfy normal distribution hypothesis. This paper presents an automated text classification model based on projection pursuit regression. The model can describe the external disciplinarian of high-dimensional data, and increase the precision of text classification. The experimental results show that the model has high recall and precision.