Download Learning Data Mining with RBy Bater Makhabel
Download Learning Data Mining with RBy Bater Makhabel
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Learning Data Mining with RBy Bater Makhabel
Download Learning Data Mining with RBy Bater Makhabel
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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
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
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.
- Sales Rank: #2340849 in Books
- Published on: 2014-12-22
- Released on: 2015-01-31
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .71" w x 7.50" l, 1.19 pounds
- Binding: Paperback
- 380 pages
About the Author
Bater Makhabel
Bater Makhabel (LinkedIn: BATERMJ and GitHub: BATERMJ) is a system architect living across Beijing, Shanghai, and Urumqi in China. He received his master's and bachelor's degrees in computer science and technology from Tsinghua University between the years 1995 and 2002. He has extensive experience in machine learning, data mining, natural language processing (NLP), distributed systems, embedded systems, the Web, mobile, algorithms, and applied mathematics and statistics. He has worked for clients such as CA Technologies, META4ALL, and EDA (a subcompany of DFR). He also has experience in setting up start-ups in China. Bater has been balancing a life of creativity between the edge of computer sciences and human cultures. For the past 12 years, he has gained experience in various culture creations by applying various cutting-edge computer technologies, one being a human-machine interface that is used to communicate with computer systems in the Kazakh language. He has previously collaborated with other writers in his fields too, but Learning Data Mining with R is his first official effort.
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