premise: Pattern recognition uses unsupervised learning to discover previously unknown 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 ) . Machine learning is the common term for supervised learning methods and originates from artificial intelligence , whereas KDD and data mining have a larger focus on unsupervised methods and stronger connection to business use . In pattern recognition , there may be a higher interest to formalize , explain and visualize the pattern , while machine learning traditionally focuses on maximizing the recognition rates .