Optimization of Entrepreneurship Education for College Students Based on Improved Random Forest Algorithm

As we all know, the random forest algorithm has advantages of high classification intensity and wide application range. Nevertheless, it still a lot room for improvement. This paper introduces basic idea working principle algorithm, so this proposes some improved algorithms on basis current research studies. College students, as most innovative adaptable group, have gradually become development direction China’s education reform to cultivate their employment ability develop education. By constructing model relationship between innovation entrepreneurship college students’ employability, examines impact mode entrepreneurship. At same time, is tested by improving algorithm. The process talent quality evaluation select talents with best comprehensive based various indicators performance in school, which can be regarded problem unbalanced data sets. proposed little difference precision recall rate when used training but certain degree improvement accuracy rate, meets design requirements.