A Study on Emotion Recognition Model Incorporating Random Forest Algorithm and Its Improvement on Information System Security Performance

The article uses the appropriate equipment for research data, designing the face and physiological signal emotion recognition network respectively, and putting its recognition features into the random forest classifier for training in order to realize the construction work of emotion recognition model.In-depth interpretation of the random forest algorithm based emotion recognition model in the application of information systems, combined with the research data, respectively, the emotion recognition model and system safety performance testing assessment.The emotion recognition model of this paper based on the 25% retention method has a recognition rate of 96.16% for the 14dimensional B emotion features, which has the highest recognition efficacy and can well meet the system emotion recognition needs.The experimental group is found to be significantly different from the control group, and it is concluded that by introducing the emotion recognition model into the traditional information system, all three security performance indicators of the system are significantly improved.