本課程從統計角度如摘要統計、次數分配圖表、比較檢定、相關及迴歸連結至分群、決策樹、類神經網路等資料採礦方法，藉由統計軟體SAS Enterprise Guide (SAS\EG) & SAS Enterprise Miner(SAS\EM) 進行巨量資料之採礦分析，培養學生從中發掘暨整合資訊的能力。This course is concerned with data mining, which is the application of the methods of statistics, data analysis and machine learning algorithms to the exploration and analysis of large data sets, with the aim of extracting new, previously unknown, and potentially useful information from the process of knowledge discovery in databases (KDD). Data mining is being applied in an increasing variety of areas, such as financial, economic, high-tech industrial, scientific and medical fields, as an essential component of decision assistance system. Students will learn the ability to analyze massive and complicated data and will be able to turn the raw data into valuable information using the software SAS Enterprise Miner (EM) and Enterprise Guide (EG). The objective of this course is to introduce statistical data mining concepts, describe methods in statistical data mining from sampling to decision trees, and provide decision support solutions.This course uses statistical software SAS Enterprise Guide (SAS\EG) & SAS Enterprise from a statistical perspective such as summary statistics, frequency distribution charts, comparison tests, correlation and regression connections to data mining methods such as clustering, decision trees, and neural networks. Miner (SAS\EM) conducts mining analysis of huge amounts of data and cultivates students' ability to discover and integrate information. This course is concerned with data mining, which is the application of the methods of statistics, data analysis and machine learning algorithms to the exploration and analysis of large data sets, with the aim of extracting new, previously unknown, and potentially useful information from the process of knowledge discovery in databases (KDD). Data mining is being applied in an increasing variety of areas, such as financial, economic, high-tech industrial, scientific and medical fields, as an essential component of decision assistance system. Students will learn the ability to analyze massive and complicated data and will be able to turn the raw data into valuable information using the software SAS Enterprise Miner (EM) and Enterprise Guide (EG). The objective of this course is to introduce statistical data mining concepts, describe methods in statistical data mining from sampling to decision trees, and provide decision support solutions.
1.曾淑峰、林志弘、翁玉麟（2012年9月），資料採礦應用—以SAS Enterprise Miner為工具，梅霖文化事業有限公司(ISBN: 978-986-6511-60-8)
2.Slaughter, S.J. and Delwiche, L.D., 蔡宏明、蔡秉諺譯（2011年11月），SAS Enterprise Guide實用工具書，梅霖文化事業有限公司(ISBN: 978-986-6511-58-5)
1. Zeng Shufeng, Lin Zhihong, and Weng Yulin (September 2012), Data Mining Application—using SAS Enterprise Miner as a tool, Meilin Cultural Industry Co., Ltd. (ISBN: 978-986-6511-60-8)
2.Slaughter, S.J. and Delwiche, L.D., translated by Cai Hongming and Cai Bingyan (November 2011), SAS Enterprise Guide practical reference book, Meilin Cultural Enterprise Co., Ltd. (ISBN: 978-986-6511-58-5)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 作業作業 Homework |
30 | Homeworks (單元資料庫實作) |
| 計畫報告計畫報告 project report |
30 | Project Report (PPT口頭報告+Word書面報告) |
| 期末考試期末考試 final exam |
40 | Final Exam (總複習+前瞻性創新研究論文一篇) |
