隨著網際網路以及資料庫技術的發達，人們搜尋資料變得愈來愈容易，透過網路我們可以輕易地獲取大量的資料，於是在資料充斥的情況之下，現代的資訊技術所要面臨的挑戰已經不是如何管理資料，而是如何從這些大量的資料當中，找出真正有用的資訊，而要滿足這個需求最主要的方法就是仰賴資料探勘的技術。
資料探勘是一個利用各種分析工具在大量資料中發現模型和資料間關係的過程，使用這些模型和關係可以進行預測，它幫助決策者尋找資料間潛在的關聯，發現被忽略的因素，因而認為是解當今時代所面臨的資料爆炸而資訊貧乏問題的一種有效方法。1. 資料探勘與資料探勘相關技術
2. 資料探勘相關應用軟體
3. 資料探勘在相關領域之應用With the development of Internet and database technology, it is becoming easier for people to search data. Through the Internet, we can easily obtain a large amount of data. Therefore, under the circumstances of data flooding, the challenges faced by modern information technology are no longer how to manage data, but how to find truly useful information from these large amounts of data. The most important way to meet this requirement is to rely on data exploration technology.
Data exploration is a process that uses various analytical tools to discover models and data relationships in a large amount of data. Using these models and relationships can be predicted. It helps decision makers find potential relationships between data and discover factors that are ignored, and therefore it is considered an effective way to solve the data explosion faced by this era and lack of information problems. 1. Technologies related to data exploration and data exploration
2. Application software related to data exploration
3. Application of data exploration in related fields
To equip the students with the knowledge and techniques of data mining to handle real world problems
To equip the students with the knowledge and techniques of data mining to handle real world problems
1.資料探勘 (旗標)
2.資料探勘原理與技術 (五南)
3.資料探勘理論與應用-以IBM SPSS Modeler為範例 (博碩文化)
4.資料探勘 (滄海)
1. Data Exploration (Flag)
2. Principles and Technology of Data Exploration (Wu Nan)
3. Data exploration theory and application-taking IBM SPSS Modeler as an example (Boyan Culture)
4. Data Exploration (Shaped Sea)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時成績(出席、參與及作業)平時成績(出席、參與及作業) Regular achievements (attendance, participation and work) |
30 | 5次以上無故出席0% |
| 期中考期中考 Midterm exam |
20 | |
| 分組報告分組報告 Sub-group report |
25 | |
| 期末專題報告期末專題報告 Final issue report |
25 |
