Learning Data Mining with R
Packt Publishing
Summary
Overview
Book Description: Paperback 314 pages.
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.
Description
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
Who is this course for?
Table of Contents:
1: WARMING UP
2: MINING FREQUENT PATTERNS, ASSOCIATIONS, AND CORRELATIONS
3: CLASSIFICATION
4: ADVANCED CLASSIFICATION
5: CLUSTER ANALYSIS
6: ADVANCED CLUSTER ANALYSIS
7: OUTLIER DETECTION
8: MINING STREAM, TIME-SERIES, AND SEQUENCE DATA
9: GRAPH MINING AND NETWORK ANALYSIS
10: MINING TEXT AND WEB DATA
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