Research on quality evaluation of innovation and entrepreneurship education for college students based on random forest algorithm and logistic regression model.

ABSTRACT: The quality evaluation of innovation and entrepreneurship (I&E) in the education sector is achieving worldwide attention as empowering nations with high quality talents is quintessential for economic progress. China, a pioneer in the world market in almost all sectors have transformed its educational policies and incorporated entrepreneurial skills as a part of their education models to further catalyst the country's economic progress. This research focuses on building a novel hybrid Machine Learning (ML) model by integrating two powerful algorithms namely Random Forest (RF) and Logistic Regression (LR) to assess the intensity of the I&E in education from the data acquired from 25 leading Higher Educational Institution's (HEI) in different provinces. The major contributions to the work are

SUBMITTER: Lu Q 

PROVIDER: S-EPMC10280670 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature