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Data Mining with R Learning with Case Studies


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This book is about learning how to use R for performing data mining.

The book follows a "learn by doing it" approach to data mining instead of the more frequent theoretical description of the techniques available in this discipline. This is accomplished by presenting a series of illustrative case studies for which all necessary steps, code and data are provided to the reader.

The book writing style establishes it as a good source for practical classes on data mining, but also as an attractive document to professionals working on data mining in non-academic environments.

Most of the main data mining processes and techniques are covered in the book by means of the presentation of four detailed case studies:
Predicting algae blooms
Predicting stock market returns
Detecting fraudulent transactions
Classifying microarray samples

Luis Torgo has a degree in Systems and Informatics Engineering and a PhD in Computer Science. He is currently an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto. He is also a researcher of the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) belonging to INESC Porto LA. Luis Torgo has been an active researcher in Machine Learning and Data Mining for more than 20 years. He has lead several academic and industrial Data Mining research projects. Luis Torgo accompanies the R project almost since its beginning, using it on his research activities. He teaches R at different levels and has given several courses in different countries.

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