Learning Data Mining with R
Bater Makhabel
- 出版商: Packt Publishing
- 出版日期: 2015-01-30
- 售價: $2,010
- 貴賓價: 9.5 折 $1,910
- 語言: 英文
- 頁數: 314
- 裝訂: Paperback
- ISBN: 1783982101
- ISBN-13: 9781783982103
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相關分類:
Data-mining
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相關翻譯:
R語言數據挖掘 (簡中版)
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相關主題
商品描述
Develop key skills and techniques with R to create and customize data mining algorithms
About This Book
- Develop a sound strategy for solving predictive modeling problems using the most popular data mining algorithms
- Gain understanding of the major methods of predictive modeling
- Packed with practical advice and tips to help you get to grips with data mining
Who This Book Is For
This book is intended for the budding data scientist or quantitative analyst with only a basic exposure to R and statistics. This book assumes familiarity with only the very basics of R, such as the main data types, simple functions, and how to move data around. No prior experience with data mining packages is necessary; however, you should have a basic understanding of data mining concepts and processes.
What You Will Learn
- Discover how you can manipulate data with R using code snippets
- Get to know the top classification algorithms written in R
- Develop best practices in the fields of graph mining and network analysis
- Find out the solutions to mine text and web data with appropriate support from R
- Familiarize yourself with algorithms written in R for spatial data mining, text mining, and web data mining
- Explore solutions written in R based on RHadoop projects
In Detail
Being able to deal with the array of problems that you may encounter during complex statistical projects can be difficult. If you have only a basic knowledge of R, this book will provide you with the skills and knowledge to successfully create and customize the most popular data mining algorithms to overcome these difficulties.
You will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. Discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on RHadoop projects. You will finish this book feeling confident in your ability to know which data mining algorithm to apply in any situation.
商品描述(中文翻譯)
發展使用 R 創建和自定義數據挖掘算法的關鍵技能和技巧
關於本書
- 使用最流行的數據挖掘算法,制定解決預測建模問題的可靠策略
- 瞭解主要的預測建模方法
- 提供實用的建議和技巧,幫助您掌握數據挖掘技術
本書適合對 R 和統計學只有基本了解的初學者數據科學家或量化分析師。本書假設您只熟悉 R 的基本知識,例如主要的數據類型、簡單的函數以及如何處理數據。不需要具備數據挖掘軟件的先前經驗,但您應該對數據挖掘概念和流程有基本的理解。
您將學到什麼
- 通過代碼片段瞭解如何使用 R 操縱數據
- 熟悉使用 R 編寫的頂級分類算法
- 在圖形挖掘和網絡分析領域發展最佳實踐
- 了解如何使用 R 挖掘文本和網絡數據的解決方案
- 熟悉使用 R 編寫的空間數據挖掘、文本挖掘和網絡數據挖掘算法
- 探索基於 RHadoop 項目的 R 解決方案
詳細內容
在處理複雜的統計項目中可能遇到各種問題,這可能很困難。如果您只具備基本的 R 知識,本書將為您提供成功創建和自定義最流行的數據挖掘算法以克服這些困難的技能和知識。
您將學習如何使用代碼片段操縱數據,並在使用 R 程序時介紹探索頻繁模式、關聯和相關性的挖掘。瞭解如何為各種預測模型、流數據和時間序列數據編寫代碼。您還將瞭解基於 RHadoop 項目的 R 解決方案。閱讀完本書後,您將對在任何情況下應該應用哪種數據挖掘算法充滿信心。