Behavior Prediction Based On Institutional Research Reports And Its Periodicity

Research on behavioral prediction based on institutional research and cyclicality of its holdings belongs to a relatively new field of research.This article builds an organization behavior prediction system based on stochastic forest and natural language analysis.The key points of research report are natural language understanding and many interdisciplinary subjects.The core of natural language processing is the study of textual features,which mainly includes word segmentation and text classification.Because CoreNLP has powerful syntax analysis function,random forest has good accuracy and robustness,and they can provide a good foundation for the realization of the prediction model in this paper.Therefore,by using CoreNLP segmentation tool to segment the research report and random forest Classifiers classify research reports.The forecasting model in this paper has been trained and validated by a large number of research reports,with an accuracy of 72%.The contents of this paper can provide strong support for the analysis of financial research data based on machine learning methods.