本課程以統計角度，介紹大數據與現行產業間之關聯外，並進一步介紹資料採礦工具與方法，配合統計軟體SAS Enterprise Guide 和 SAS Enterprise Miner的使用，訓練學生從大量和複雜的資料中發掘重要的決策資訊，培養同學研究與解決問題的能力。
This course introduces the methods in data mining through the statistical point of view. Students will learn the ability to analyze massive and complicated data and will be able to turn the raw data into valuable information using SAS Enterprise Guide & SAS Enterprise Miner.This course introduces the relationship between large data and current industry from a statistical perspective, and further introduces data mining tools and methods. In conjunction with the use of the SAS Enterprise Guide and SAS Enterprise Miner, students explore important decision information from a large number of and complex data, and cultivate students' ability to research and solve problems.
This course introduces the methods in data mining through the statistical point of view. Students will learn the ability to analyze massive and complicated data and will be able to turn the raw data into valuable information using SAS Enterprise Guide & SAS Enterprise Miner.
智聯網時代的來臨，改變資料蒐集與儲存的技術，加速資料的取得與累積，大幅改變資料的應用方式。「大數據」(Big Data)或稱「巨量資料」的分析與資料挖礦，4V即指用以取決巨量資料的整備度：巨量（Volume）、高速（Velocity）、多樣（Variety）、價值（Value），完整無遺地掌握巨量資料4V，就能從混沌的巨量資料邁向進階的巨量資料分析。大數據分析的基礎與應用為統計與資料分析方法，進進一步利用統計資料挖礦，發掘先前未知且潛在有用的資訊樣型，進而轉化為有價值的資訊或知識，此外在巨量資料的環境下，許多的應用情境需要在未儲存資料前就要採取行動，以符合現在環境需求。課程內容含括資料預處理、資料挖礦入門、資料挖礦技術與軟體實作，依序介紹SAS Enterprise Guide (SAS/EG)和SAS Enterprise Miner(SAS/EM)，同時希望完成課程時，能協助學生：(1)通過SAS Enterprise Guide 檢測，具足資料整理、合併檔案、欄位新增、資料彙總以及報表製作這五大面向，(2) 製作專業化巨量資料視覺分析簡報，(3)精熟資料挖礦技術，如關聯法則、決策樹分析、集群分析、迴歸分析、和模型選擇與整合。除依序介紹資料挖礦的工具與方法外，著重利用專案及軟體操作訓練同學研究與解決問題的能力。
In the era of smart network, we have changed the technology of data collection and storage, accelerated the acquisition and accumulation of data, and significantly changed the application method of data. "Big Data" or "big data" analysis and data mining. 4V refers to the overall preparation used to determine the huge amount of data: large amount (Volume), high speed (Velocity), variety (Variety), value (Value). If you master the huge amount of data completely and without any limit, you can go from chaotic huge amount of data to advanced huge amount of data analysis. The basic and application of large data analysis is a statistical and data analysis method. We further use statistical data mining to mine, discover previously unknown and potentially useful information types, and then convert them into valuable information or knowledge. In addition, in an environment of huge amounts of data, many application situations need to take action before data is stored to meet current environmental needs. The course content includes data pre-processing, data mining entry, data mining technology and software implementation, and introduces SAS Enterprise Guide (SAS/EG) and SAS Enterprise Miner (SAS/EM) in sequence. At the same time, we hope to help students when completing the course: (1) Through SAS Enterprise Guide detection, we have the five major aspects of data sorting, merging files, adding fields, data summary and report production, (2) Making professional and massive data visual analysis briefs, (3) Proficient in data mining techniques, such as correlation methods, decision tree analysis, cluster analysis, replication analysis, and model selection and integration. In addition to introducing the tools and methods of data mining in sequence, we focus on using projects and software operation training peers' ability to research and solve problems.
1. Tan, Steinbach and Kumar, Introduction to Data Mining, Addison Wesley, 2006. (歐亞)
2. 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)
3. 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. Tan, Steinbach and Kumar, Introduction to Data Mining, Addison Wesley, 2006. (Europe)
2. Zeng Shufeng, Lin Zhihong, Weng Yulin (September 2012), data mining application—using SAS Enterprise Miner as a tool, Meilin Culture Industry Co., Ltd. (ISBN: 978-986-6511-60-8)
3. Slaughter, S.J. and Delwiche, L.D., Cai Hongming and Cai Bing-san (November 2011), SAS Enterprise Guide practical tools book, Meilin Cultural Affairs Co., Ltd. (ISBN: 978-986-6511-58-5)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|
