本課程希望培養學生對於data mining相關的理論方法與實務問題解決的能力
課程主要涵蓋資料處理、分類、關係、分群等方法，並透過實際問題分析與探討，
了解各個方法如何應用到真實世界的資料處理，進而有能力提供真實問題的解決方法.This course hopes to cultivate students' ability to solve theoretical methods and practical problems related to data mining
The course mainly covers data processing, classification, relationship, grouping and other methods, and through actual problem analysis and exploration,
Understand how each method can be applied to the real world of data processing, and then be able to provide real-world solutions.
讓學生知悉資料探勘如何運作，原理為何
Let students know how data exploration works and what principles
1. Introduction to Data Mining
Pang-Ning Tan, Michigan State University,
Michael Steinbach, University of Minnesota
Vipin Kumar, University of Minnesota
Addison-Wesley, 2006.
2. 資料探勘
施雅月、賴錦慧譯,
歐亞書局有限公司, ISBN: 978-9860154-657-5
1. Introduction to Data Mining
Pang-Ning Tan, Michigan State University,
Michael Steinbach, University of Minnesota
Vipin Kumar, University of Minnesota
Addison-Wesley, 2006.
2. Data Exploration
Shi Yayue, Feng Qing Huilu,
European Books Bureau Co., Ltd., ISBN: 978-9860154-657-5
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 課堂參與課堂參與 Class Participation |
20 | 點名、課堂討論互動、特定議題意見表達 |
| 期中報告期中報告 Midterm Report |
40 | |
| 期末專題實作與報告期末專題實作與報告 Final period topic implementation and report |
40 |
