premise: Pattern recognition is used strictly on known patterns.
hypothesis: 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 labeled `` training '' data ( supervised learning ) , but when no labeled data are available other algorithms can be used to discover previously unknown patterns ( unsupervised learning ) . A common example of a pattern-matching algorithm is regular expression matching , which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors . In contrast to pattern recognition , pattern matching is generally not considered a type of machine learning , although pattern-matching algorithms ( especially with fairly general , carefully tailored patterns ) can sometimes succeed in providing similar-quality output of the sort provided by pattern-recognition algorithms .