Predictive Analysis and Research Of Python Usage Rate Based on Polynomial Regression Model

Abstract

Nowadays, more and more people will choose Python to help them accomplish some things, in order to better predict the proportion of Python usage. This paper proposes a polynomial regression analysis model. First, crawl the historical usage data of the python language from the official website; then clean the analysis, use a scatter plot to visualize the relationship between tags and features; then use the training set data to train the polynomial regression Model; Finally, the generalization ability of the model is tested through the test set. After many experiments, it can be known that when the highest number is 9 times, the entire training set score is 0.912862, and the test set score is 0.886600, which achieves a better fitting effect and has a certain practical value, which can be used for popularization.