Predictive Analysis and Research Of Python Usage Rate Based on Polynomial Regression Model
Yang Gong, Pan Zhang · 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture (AIAM) · 2021
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.