A Boosting Regression-Based Method to Evaluate the Vital Essence in Semiconductor Industry Performance

Ping Yu Hsu, I. Wen Yeh, Ching Hsun Tseng, Shin Jye Lee*

*Corresponding author for this work

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

In accordance with the statistical analysis, the industrial performance is usually related to research and development (RD) 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 article 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 RD intensity, actually sway the gross net value in the annual financial announcement of semiconductor industries. Moreover, this article proposes another concept to evaluate the essential factor contributing the development of semiconductor industries. Instead of only focusing on the effect of RD intensity, this article also predicts the future growth rate (GR) of net value by applying the greedy search of XGBoost Regression.

原文English
文章編號9177120
頁(從 - 到)156208-156218
頁數11
期刊IEEE Access
8
DOIs
出版狀態Published - 2020

指紋 深入研究「A Boosting Regression-Based Method to Evaluate the Vital Essence in Semiconductor Industry Performance」主題。共同形成了獨特的指紋。

引用此