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R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for;
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sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data;
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Mine valuable insights from your data using popular tools and techniques in R About This Book * Understand the basics of data mining;
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Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining;
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Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining;
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and;
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demonstrating the internal operation and usage of data mining algorithms using examples in R.;
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and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and;
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Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) presents an applied and interactive approach to;
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an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and analytics with R, then this book;
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Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a do-it-yourself approach;
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Despite being a young field of research and development, data mining has proved to be a successful approach to extracting knowledge from;
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. R is much more powerful and is a commercially viable data mining tool. We also demonstrate WEKA, which is a highly useful academic software;
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introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are;
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data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications Visualize data with;
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With its state-of-the-art capabilities for rapidly processing and retrieving huge quantities of data, Microsoft(R) SQL Server 2000;
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analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big;
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8627A-4 Finally, here's a book that explains in plain English what data mining is and how it's used to improve a company's bottom line;
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mining implementation using R and Rattle open source data mining tools. . Technical topics discussed in the book include: * Emerging Research;
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data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics;
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then transform that data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications;
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that can provide marketers with detailed information about the products, content, and services their customers desire. Data Mining Mobile;
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that can provide marketers with detailed information about the products, content, and services their customers desire. Data Mining Mobile;
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Write functions with R for data science, data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using;
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Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying;
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Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying;
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-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. You;
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