Pattern Recognition

Pattern recognition is a branch of machine learning that focuses on the recognition of patterns and regularities in data, although it is in some cases considered to be nearly synonymous with machine learning. Pattern recognition systems are in many cases trained from labelled "training" data, but when no labelled data are available other algorithms can be used to discover previously unknown patterns (unsupervised learning) Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to perform "most likely" matching of the inputs, taking into account their statistical variation. This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns In contrast to pattern recognition; pattern matching is generally not considered a type of machine learning, although pattern-matching algorithms can sometimes succeed in providing similar-quality output of the sort provided by pattern-recognition algorithms.

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