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 analysis and discussion of practical problems,
Understand how each method is applied to real-world data processing, and then be able to provide solutions to real problems.
讓學生知悉資料探勘如何運作，原理為何
Let students know how data mining works and what its principles are.
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
Translated by Shi Yayue and Lai Jinhui,
Eurasian Book Company 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 interim report |
40 | |
| 期末專題實作與報告期末專題實作與報告 Final project implementation and report |
40 |
