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Data mining r language combat pdf free version

Software Description

Installation tutorial

The pdf version of the data mining r language combat is collected from the Internet by the editors, and is designed to provide convenient learning for the majority of users. This book focuses on the use of R for data mining, focusing on the data mining process of R, the use of algorithm packages and related tools Applications.

Introduction of data mining r language combat pdf version:
Combined with a large number of selected data mining examples, the R software is deeply dived out and comprehensively introduced, so that readers can deeply understand the essence of R and quickly, efficiently and flexibly master the skills of using R for data mining. By reading the actual data mining r language, readers can not only master the method of using R and related algorithm packages to quickly solve practical problems, but also get a comprehensive start from the analysis of actual problems, use R to solve, and analyze the mining results. training.
Introduction:
R is a free and open source software, which provides the best statistical calculation and plotting functions, especially a large number of data mining algorithm packages, making it an excellent and rare data mining tool software. The main purpose of this book is to introduce readers to how to use R for data mining. Through a large number of selected examples, the application of R in the field of data mining is described step by step and comprehensively and systematically.
The actual combat of data mining r language is based on three parts: data preprocessing, basic algorithms and applications, and advanced algorithms and applications.
(1) Part I: Data Preprocessing '
It consists of chapters 1-5. First, it briefly introduces the data mining process, algorithms, and tools. Then it introduces the data classification and data set in R, and the various flexible methods for obtaining data using R. Finally, the methods of exploratory analysis and preprocessing of data are described. These contents are the most basic content for data mining using R.
(2) Part I: Basic Algorithms and Applications
It consists of chapters 6-9. It mainly describes the basic algorithms and applications of data mining, including association analysis, cluster analysis, discriminant analysis, and decision trees. These algorithms are also the most commonly used algorithms for data mining. R provides a rich and powerful algorithm package and implementation functions, which must be mastered by primary and intermediate users of data mining.
(3) Next: Advanced Algorithms and Applications
It consists of chapters 10-14, mainly about advanced algorithms and applications of data mining, including integrated learning, random forest, support vector machines, and neural networks, and the use of tools in R to evaluate and select data mining models. For intermediate and advanced users, you can learn more about this article.

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