Research on BP neural network model based on feature engineering

This research used the machine learning algorithm of the BP neural network to predict a data set. In order to verify the performance of the prediction model, we introduce the confusion matrix and F1 score to evaluate the effect of machine learning. In order to optimize the BP neural network model, we use feature engineering to process the data set and apply the BP neural network model to this new data set. The experimental results show that the machine learning performance of the BP neural network model based on feature engineering is improved.