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Describes important statistical ideas in machine learning, data mining, and bioinformatics. Covers a broad range, from supervised learning (prediction), to unsupervised learning, including classification trees, neural networks, and support vector machines.
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Previews available in: English
Subjects
Supervised learning (Machine learning), Database management, Artificial Intelligence (incl. Robotics), Statistics, Artificial intelligence, Biology, Data processing, Computer science, Mathematical statistics, Computer Appl. in Life Sciences, Probability and Statistics in Computer Science, Statistical Theory and Methods, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Computational biology--methods, Statistics as topic--methods, Data interpretation, statistical, Q325.75 .h37 2001, 006.3/1, Computational Biology, Methods, Statistics as Topic, Statistical Data InterpretationEdition | Availability |
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1
Elements of Statistical Learning: Data Mining, Inference, and Prediction
2013, Springer London, Limited
in English
0387216065 9780387216065
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
Nov 01, 2008, Springer
paperback
0387848843 9780387848846
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The elements of statistical learning: data mining, inference, and prediction : with 200 full-color illustrations
2001, Springer
in English
0387952845 9780387952840
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The elements of statistical learning: data mining, inference, and prediction
2001, Springer
in English
0387952845 9780387952840
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Book Details
Edition Notes
Includes bibliographical references (p. [509]-522) and indexes.
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Community Reviews (0)
August 20, 2024 | Edited by MARC Bot | import existing book |
December 19, 2023 | Edited by ImportBot | import existing book |
May 16, 2023 | Edited by loopkid | Corrected capitalization and authors |
December 8, 2022 | Edited by MARC Bot | import existing book |
December 10, 2009 | Created by WorkBot | add works page |