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Pattern recognition

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Abstract We give an overview of pattern recognition, concentrating on the problem of pattern classification. Several popular discrimination methods are reviewed using decision theory as a unifying framework. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition

The joint distribution of class J and feature vector X, when there are two classes, and the feature vector dimension is one. The first panel shows a jittered scatter plot of (X, J), the middle panel shows the class conditional densities f1 and f2 as well as the marginal density fX, whereas the last panel shows the two posterior probabilities. The prior probabilities are P1 = 0.6 and P2 = 1 − P1.

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A multilayer perceptron with one layer of hidden units.

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Decision regions obtained using QDA (left) and the 1‐nearest neighbor classifier (right) for the same training data.

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Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition

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