R and Data Mining

A Senior Data Mining Analyst in Australia Government since 2009. Before joining public sector, he was an Australian Postdoctoral Fellow (Industry) in the Faculty of Engineering & Information Technology at University of Technology, Sydney, Australia. His research interests include clustering, association rules, time series, outlier detection and data mining applications and he has over forty papers published in journals and conference proceedings. He is a member of the IEEE and a member of the Institute of Analytics Professionals of Australia, and served as program committee member for more than thirty international conferences.

出版者:Academic Press

作者:Yanchang Zhao

页数:256

出版时间:2013-1-31

价格:GBP 55.00

装帧:Hardcover

isbn号码:9780123969637

图书标签:R数据挖掘统计DataMIning数据分析人工智能&数据挖掘计算机技术r

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. It presents an introduction into using R for data mining applications, covering most popular data mining techniques. It provides code examples and data so that readers can easily learn the techniques. It features case studies in real-world applications to help readers apply the techniques in their work.

用户评价

翻过，借鉴过里面tweet聚类的段子，也是实战型的。

翻过，借鉴过里面tweet聚类的段子，也是实战型的。

翻过，借鉴过里面tweet聚类的段子，也是实战型的。

Practical.

这本书要看全版，后边的几个案例和给出的一些在线资源还是很有价值的。