premise: Pattern recognition systems are deleted from labeled "training" data.
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 ) .