Pattern recognition uses unsupervised learning to discover previously unknown patterns .
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 track related known patterns ( partially supervised learning ) .