Intelligent Text Location Based on Multi Model Fusion

In order to reduce the additional learning burden and efficiency of people when looking for information. This paper mainly combines the prediction results of bagging, random forest and linear regression models, and builds a model to understand natural language problems and retrieve related materials. In the process of building the model, the improved data processing method is used to process the data, and then the data is imported into different models for training. This paper uses the multi-model fusion algorithm to output the predicted results, which can prevent the prediction from over-fitting And improve the accuracy of positioning.