本課程將提供在統計資料採礦會用到的工具和技巧，包含探索性數據分析、監督機器學習、非監督機器學習和模型評估。透過R程式語言培養學生靈活運用線性模型、決策樹、類神經網路、集群分析及關聯分析等資料採礦方法，讓本課程學生掌握數據分析及有效決策的能力。

This course will provide tools and techniques used in statistical data mining, including exploratory data analysis, supervised machine learning, unsupervised machine learning, and model evaluation. Through the R programming language, students are trained to flexibly use data mining methods such as linear models, decision trees, neural networks, cluster analysis, and correlation analysis, so that students in this course can master the ability of data analysis and effective decision-making.

統計資料採礦主要應用統計方法、資料分析和機器學習演算法，進行資料庫之知識挖掘，藉此從高維度大型資料庫中挖掘潛藏的有用資訊。目前已在金融、經濟、行銷、電子商務、數位資訊產業、高科技產業、生命科學和醫學等不同領域，逐漸提升地位成為決策輔助系統中的重要元件之一，提供管理階層決策輔助之用。

Statistical data mining mainly applies statistical methods, data analysis and machine learning algorithms to conduct knowledge mining in databases, thereby mining useful information hidden in high-dimensional large databases. At present, it has gradually improved its status and become one of the important components in decision-making assistance systems in different fields such as finance, economics, marketing, e-commerce, digital information industry, high-tech industry, life sciences and medicine, providing management decision-making assistance.

"An Introduction to Statistical Learning with Applications in R" by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

The book's website is http://faculty.marshall.usc.edu/gareth-james/ISL/

You are able to access the book online from the THU library http://webpac.lib.thu.edu.tw/bookDetail.do?id=959395

"An Introduction to Statistical Learning with Applications in R" by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

The book's website is http://faculty.marshall.usc.edu/gareth-james/ISL/

You are able to access the book online from the THU library http://webpac.lib.thu.edu.tw/bookDetail.do?id=959395