Pattern recognition as a quest for minimum entropy
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摘要
We shall show that many known algorithms of clustering and pattern recognition can be characterized as efforts to minimize entropy, when suitably defined.
论文关键词：Pattern recognition,Clustering,Algorithm,Entropy,Learning theory,Fisher's discriminant,Coalescence model,Karhunen-Loève expansion,Diday-Lemoine's criterion
论文评审过程：Received 27 January 1981, Available online 19 May 2003.
论文官网地址：https://doi.org/10.1016/0031-3203(81)90094-7
