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Due to the everincreasing complexity and size of todays data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis. A completely new addition in the second edition is a chapter on how to avoid false discoveries and produce valid results, which is novel among other contemporary textbooks on data mining. Data mining and business analytics with r utilizes the open source software r for the analysis, exploration, and simplification of large highdimensional data sets. There are more than 1 million books that have been. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data.
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