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'''Cluster analysis''' or '''clustering''' is a common technique for [[statistics|statistical]] [[data analysis]], which is used in many fields, including [[machine learning]], [[data mining]], [[pattern recognition]], [[image analysis]] and [[bioinformatics]]. Clustering is the [[classification]] of similar objects into different groups, or more precisely, the [[partition of a set|partitioning]] of a data set into [[subset]]s (clusters), so that the data in each subset (ideally) share some common trait - often proximity according to some defined [[metric (mathematics)|distance measure]]. |
'''Cluster analysis''' or '''clustering''' is a common technique for [[statistics|statistical]] [[data analysis]], which is used in many fields, including [[machine learning]], [[data mining]], [[pattern recognition]], [[image analysis]] and [[bioinformatics]]. Clustering is the [[classification]] of similar objects into different groups, or more precisely, the [[partition of a set|partitioning]] of a data set into [[subset]]s (clusters), so that the data in each subset (ideally) share some common trait - often proximity according to some defined [[metric (mathematics)|distance measure]]. |
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+ | Machine learning typically regards data clustering as a form of [[unsupervised learning]]. |
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Besides the term ''data clustering'' (or just ''clustering''), there are a number of terms with similar meanings, including ''cluster analysis'', ''automatic classification'', ''numerical taxonomy'', ''botryology'' and ''typological analysis''. |
Besides the term ''data clustering'' (or just ''clustering''), there are a number of terms with similar meanings, including ''cluster analysis'', ''automatic classification'', ''numerical taxonomy'', ''botryology'' and ''typological analysis''. |