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* |description=人工智能，数据挖掘，模型评估

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'''机器学习 Machine Learning（ML）'''是计算机科学的分支——[[人工智能]]的一个子集，它通常使用统计学方法，借助数据，赋予计算机“学习”的能力（例如，逐渐提高在特定任务上的表现）而不需要明确编写学习过程<ref name =" 2w">The "without being explicitly programmed" definition is often attributed to Arthur Samuel, who coined the term "machine learning" in 1959. But the phrase is not found literally in this publication, and may be a paraphrase that appeared later. Confer "Paraphrasing Arthur Samuel (1959), the question is: How can computers learn to solve problems without being explicitly programmed?" in Koza, John R.; Bennett, Forrest H.; Andre, David; Keane, Martin A. (1996). [https://link.springer.com/chapter/10.1007/978-94-009-0279-4_9 Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming]. Artificial Intelligence in Design '96. Springer, Dordrecht. pp. 151–170. [https://doi.org/10.1007/978-94-009-0279-4_9 doi:10.1007/978-94-009-0279-4_9] </ref>。

'''机器学习 （Machine Learning）（ML）'''是计算机科学的分支——[[人工智能]]的一个子集，它通常使用统计学方法，借助数据，赋予计算机“学习”的能力（例如，逐渐提高在特定任务上的表现）而不需要明确编写学习过程<ref name =" 2w">The "without being explicitly programmed" definition is often attributed to Arthur Samuel, who coined the term "machine learning" in 1959. But the phrase is not found literally in this publication, and may be a paraphrase that appeared later. Confer "Paraphrasing Arthur Samuel (1959), the question is: How can computers learn to solve problems without being explicitly programmed?" in Koza, John R.; Bennett, Forrest H.; Andre, David; Keane, Martin A. (1996). [https://link.springer.com/chapter/10.1007/978-94-009-0279-4_9 Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming]. Artificial Intelligence in Design '96. Springer, Dordrecht. pp. 151–170. [https://doi.org/10.1007/978-94-009-0279-4_9 doi:10.1007/978-94-009-0279-4_9] </ref>。

<br>''机器学习''的名字是Arthur Samuel<ref name="Samuel">{{Cite journal|last=Samuel|first=Arthur|date=1959|title=Some Studies in Machine Learning Using the Game of Checkers|journal=IBM Journal of Research and Development|volume=3|issue=3|pages=210–229}}</ref>  

<br>''机器学习''的名字是Arthur Samuel<ref name="Samuel">{{Cite journal|last=Samuel|first=Arthur|date=1959|title=Some Studies in Machine Learning Using the Game of Checkers|journal=IBM Journal of Research and Development|volume=3|issue=3|pages=210–229}}</ref>  

==拓展阅读==

==拓展阅读==

*    Nils J. Nilsson, [http://ai.stanford.edu/people/nilsson/mlbook.html Introduction to Machine Learning.]

*    Nils J. Nilsson, [http://ai.stanford.edu/people/nilsson/mlbook.html Introduction to Machine Learning.]

*   Trevor Hastie, Robert Tibshirani and Jerome H. Friedman (2001). [https://web.stanford.edu/~hastie/ElemStatLearn/ The Elements of Statistical Learning], Springer. ISBN 0-387-95284-5.

* Trevor Hastie, Robert Tibshirani and Jerome H. Friedman (2001). [https://web.stanford.edu/~hastie/ElemStatLearn/ The Elements of Statistical Learning], Springer. ISBN 0-387-95284-5.

*   Pedro Domingos (September 2015), [https://en.wikipedia.org/wiki/The_Master_Algorithm The Master Algorithm], Basic Books, ISBN 978-0-465-06570-7

* Pedro Domingos (September 2015), [https://en.wikipedia.org/wiki/The_Master_Algorithm The Master Algorithm], Basic Books, ISBN 978-0-465-06570-7

*   Ian H. Witten and Eibe Frank (2011). Data Mining: Practical machine learning tools and techniques Morgan Kaufmann, 664pp., ISBN 978-0-12-374856-0.

* Ian H. Witten and Eibe Frank (2011). Data Mining: Practical machine learning tools and techniques Morgan Kaufmann, 664pp., ISBN 978-0-12-374856-0.

*   Ethem Alpaydin (2004). Introduction to Machine Learning, MIT Press, ISBN 978-0-262-01243-0.

* Ethem Alpaydin (2004). Introduction to Machine Learning, MIT Press, ISBN 978-0-262-01243-0.

*   David J. C. MacKay. [http://www.inference.org.uk/mackay/itila/book.html Information Theory, Inference, and Learning Algorithms] Cambridge: Cambridge University Press, 2003. ISBN 0-521-64298-1

* David J. C. MacKay. [http://www.inference.org.uk/mackay/itila/book.html Information Theory, Inference, and Learning Algorithms] Cambridge: Cambridge University Press, 2003. ISBN 0-521-64298-1

*   Richard O. Duda, Peter E. Hart, David G. Stork (2001) Pattern classification (2nd edition), Wiley, New York, ISBN 0-471-05669-3.

* Richard O. Duda, Peter E. Hart, David G. Stork (2001) Pattern classification (2nd edition), Wiley, New York, ISBN 0-471-05669-3.

*   Christopher Bishop (1995). Neural Networks for Pattern Recognition, Oxford University Press. ISBN 0-19-853864-2.

* Christopher Bishop (1995). Neural Networks for Pattern Recognition, Oxford University Press. ISBN 0-19-853864-2.

*   Stuart Russell & Peter Norvig, (2002). Artificial Intelligence – A Modern Approach. Prentice Hall, ISBN 0-136-04259-7.

* Stuart Russell & Peter Norvig, (2002). Artificial Intelligence – A Modern Approach. Prentice Hall, ISBN 0-136-04259-7.

*    Ray Solomonoff, An Inductive Inference Machine, IRE Convention Record, Section on Information Theory, Part 2, pp., 56–62, 1957.

*    Ray Solomonoff, An Inductive Inference Machine, IRE Convention Record, Section on Information Theory, Part 2, pp., 56–62, 1957.

*    Ray Solomonoff, [http://world.std.com/~rjs/indinf56.pdf An Inductive Inference Machine] A privately circulated report from the 1956 Dartmouth Summer Research Conference on AI.

*    Ray Solomonoff, [http://world.std.com/~rjs/indinf56.pdf An Inductive Inference Machine] A privately circulated report from the 1956 Dartmouth Summer Research Conference on AI.