Chapter 1. Warming Up
In this chapter, you will learn basic data mining terms such as data definition, preprocessing, and so on.
The most important data mining algorithms will be illustrated with R to help you grasp the principles quickly, including but not limited to, classification, clustering, and outlier detection. Before diving right into data mining, let's have a look at the topics we'll cover:
- Data mining
- Social network mining
- Text mining
- Web data mining
- Why R
- Statistics
- Machine learning
- Data attributes and description
- Data measuring
- Data cleaning
- Data integration
- Data reduction
- Data transformation and discretization
- Visualization of results
In the history of humankind, the results of data from every aspect is extensive, for example websites, social networks ...
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