Practical Machine Learning Tools and Techniques Witten, Ian H Primary Author Frank, Eibe Primary Author Hall, Mark A Primary Author Pal, Christopher J Primary Author mixed material bibliography Cambridge, MA, United States Morgan Kaufmann 2017 en English

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xxxii, 621 pages : Illustrations ; 23 cm Data Mining: Practical Machine Learning Tools and Techniques, Fourth 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 fourth 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. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Data Mining 006.312 9780128042915 e-Library Universitas Pertamina Be Global Leader 006.312 WIT d 9540/PUP/2020 Perpustakaan Universitas Pertamina 006.312 WIT d c.1 9805/PUP/2020 Perpustakaan Universitas Pertamina 006.312 WIT d c.2 Data_Mining_Practical_Machine_Learning_Tools_and_Techniques.jpg 5139 2023-02-23 11:46:21 2023-02-23 14:32:33 machine generated