In accordance with the statistical analysis, the industrial performance is usually related to research and development (R&D) intensity, and this factor indeed plausibly brings the biggest profit with patents and supporting products to the development of semiconductor industry. How to evaluate the completive performance of modern industries is an increasing issue, especially for the semiconductor industries in these decades. However, almost every traditional statistical model is deterred by the hypothesis of population and independent correlation among each feature, and this makes the result of typical regression model potentially lose reliability. To avoid this weakness, this paper therefore applies a gradient boosting based method-XGBoost to evaluate the feature importance of semiconductor industries. In the simulation experiments, different findings revel certain information, apart from R&D intensity, actually sway the gross net value in the annual financial announcement of semiconductor industries. Moreover, this paper proposes another concept to evaluate the essential factor contributing the development of semiconductor industries. Instead of only focusing on the effect of R&D intensity, this paper also predicts the future growth rate (GR) of net value by applying the greedy search of XGBoost Regression. INDEX TERMS XGBoost, Boosting Regression, Semiconductor Industry I. INOTRODUCTION Research and development (R&D) management is one of important issues in the research field of human resource management (HRM), and how to make proper investment in the expense of R&D management has become an increasing issue. The most works reveal a common conclusion in the literature that R&D has a positive effect on the performance of industries, so the term "R&D Intensity" is primarily applied in the analysis of relevant works and defined as the