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Pattern recognition algorithms are used to decide, for example, if a certain fish is salmon or sea bass, given the fish's width and lightness (Duda, 2000). Pattern recognition is the process of examining a pattern (e.g., the given width-lightness measurements) and assigning a class (e.g., salmon or sea bass) using a classifier (e.g., a rule based on the location of a graphical representation of the given sample with respect to other samples of the known class). Pattern recognition is used in diverse applications: handwriting recognition, financial analysis, gene expression, biometrics, and so on. A simple, yet applicable, example of a pattern recognition algorithm is the linear classifier. This is best understood by looking at two-dimensional examples in which patterns are represented as points and the classifier is represented as a straight line.

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      EUN,LOM,LRE4,work-cmr-id:398607,http://demonstrations.wolfram.com:http://demonstrations.wolfram.com/PatternRecognitionPrimer/,ilox,learning resource exchange,LRE metadata application profile,LRE

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