Machine Learning: The State of the Art

Machine Learning: The State of the Art
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机器学习:最先进的技术

DOI:
10.1109/mis.2008.107
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发表时间:
2008-11
期刊:
IEEE Intelligent Systems and Their Applications
影响因子:
--
通讯作者:
Qing Tao
Qing Tao
中科院分区:
其他
文献类型:
--
作者:
Jue Wang;Qing Tao

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The two fundamental problems in machine learning (ML) are statistical analysis and algorithm design. The former tells us the principles of the mathematical models that we establish from the observation data. The latter defines the conditions on which implementation of data models and data sets rely. A newly discovered challenge to ML is the Rashomon effect, which means that data are possibly generated from a mixture of heterogeneous sources. A simple classification standard can shed light on emerging forms of ML. This article is part of a special issue on AI in China.
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