| Summary: | 碩士 === 國立交通大學 === 工業工程與管理系所 === 105 === Taiwanese semiconductor industry has occupied an important position in the world. Number of Taiwanese companies, however, is fewer and fewer because of rising of Chain. Meanwhile, many software vendors are spending their efforts on business intelligence to help firms keep more competitive and earn more profit. In order to help Taiwanese IC design industries find key performance indicators (KPIs). In other hand, large corporations would like to improve themselves for worldwide market as well.
This study uses the balanced scorecard (BSC) to set 25 predictors. In particular, a two-phase approach is adopted to conduct feature selection. In performance regression, Multiple Linear Regression (MLR), Multivariate Adaptive Regression Splines (MARS), Classification and Regression Tree (CART), and Random Forest (RF) are compared. Then uses the best performance regression which has the lowest Mean Squared Error (MSE). Furthermore, performance simulation is conducted by using Support Vector Regression (SVR), respectively.
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