Applied Unsupervised Learning with R P 320 p. 19

著者：Malik, Alok/Tuckfield, Bradford

【重要事項説明】

1.	手配先によって価格が異なります。
2.	納期遅延や入手不能となる場合がございます。
3.	海外のクリスマス休暇等、お正月等の長期休暇時期の発注は、納期遅延となる場合がございます。
4.	天候（国内・海外）により空港の発着・貨物受入不能の発生により納期遅延となる場合がございます。
5.	複数冊数のご注文の場合、分納となる場合がございます。
6.	美品のご指定は承りかねます。

手配先：海外仕入UK他

• 現地価格：£27.99
• お届けまでの予想日数： 6週間～7週間
• 在庫数：在庫なし
• 組合員価格：¥6,578 (税込)

手配先：海外仕入USA

• 現地価格：$38.99
• お届けまでの予想日数： 2週間～3週間
• 在庫数：112
• 組合員価格：¥7,106 (税込)

内容の説明

Design clever algorithms that find hidden patterns and draw responses from unstructured, unlabeled data About This Book * Build state-of-the-art algorithms and relate them to business problems *Learn to find patterns in your data that you didn't know existed *Revise key concepts with hands-on exercises using real-world datasets Who This Book Is For Applied Unsupervised Learning with R is designed for business professionals, who want to learn about methods to understand their data better, and developers, who have an interest in unsupervised learning. It'll help you to have basic, beginner-level familiarity with R, including how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should know basic mathematical concepts, such as exponents, square roots, means, and medians. What You Will Learn * Implement clustering methods: k-means, agglomerative, and divisive *Write code in R to analyze market segmentation and consumer behavior rules *Estimate distribution and probabilities of different outcomes *Implement dimension reduction using principal component analysis *Apply anomaly detection methods to detect frauds *Design different algorithms with R, edit and improve the code In Detail Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and all features of R that enable you to understand your data better and get answers to all your business questions. This book begins with the most important and common method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Then, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with instruction for how to work with, edit, and improve the R code. You'll also find useful tips for applying t

登録情報

商品コード：1029168590
出版社: Packt Publishing Ltd.
出版年月: 2019/03
ISBN-10: 1789956390
ISBN-13: 978-1-78995-639-9
出版国: イギリス
装丁: paper/Kt./br.
媒体: 冊子
ページ数: 320 p.
ジャンル: 人工知能