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Автор: Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal, James R. Foulds
Издательство: Morgan Kaufmann/Elsevier
Год: 2026
Страниц: 688
Язык: английский
Формат: epub (true)
Размер: 27.5 MB
Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in Machine Learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and Machine Learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Machine Learning provides the technical basis of data mining. It is used to extract information from the raw data in databases—information ideally expressed in a comprehensible form and that can be used for a variety of purposes. The process is one of abstraction, taking the data, warts and all, and inferring whatever structure underlies it. This book is about the tools and techniques of Machine Learning that are used in practical data mining for finding and, if possible describing, structural patterns in data.