Sometimes different terms are used to describe the corresponding supervised and unsupervised learning procedures for the same type of output. The unsupervised equivalent of classification is normally known as clustering, based on the common perception of the task as involving no training data to speak of, and of grouping the input data into clusters based on some inherent similarity measure (e.g. the distance between instances, considered as vectors in a multi-dimensional vector space), rather than assigning each input instance into one of a set of pre-defined classes. In some fields, the terminology is different. In community ecology, the term classification is used to refer to what is commonly known as "clustering".
sometimes different terms are used to describe the corresponding supervised and unsupervised learning procedures for the same type of output the unsupervised equivalent of classification is normally known as clustering based on the common perception of the task as involving no training data to speak of and of grouping the input data into clusters based on some inherent similarity measure (eg the distance between instances considered as vectors in a multi-dimensional vector space) rather than assigning each input instance into one of a set of pre-defined classes in some fields the terminology is different in community ecology the term classification is used to refer to what is commonly known as "clustering"