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Cluster analysis
Cluster analysis

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!!! Overview
[{$pagename}] is the task of [classification] in such a way that objects in the same [classification] (called a cluster) are more similar (in some sense or another) to each other than to those in other [classifications] (clusters).
[{$pagename}] is a form of [Unsupervised Learning]
[{$pagename}] is a common technique for exploratory data mining, statistical data analysis, used in many fields, including [machine Learning], [pattern-recognition], [computer vision], information retrieval, [bioinformatics], [data] compression, and computer graphics.
[{$pagename}] itself is not one specific [algorithm], but the general task to be solved. [{$pagename}] can be achieved by various [algorithms] that differ significantly in their notion of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include [classifications] with small distances among the cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-objective optimization problem. The appropriate clustering [algorithm] and [parameter] settings (including values such as the distance function to use, a density threshold or the number of expected clusters) depend on the individual [data] set and intended use of the results.
[{$pagename}] as such is not an automatic task, but an iterative process of knowledge discovery or interactive multi-objective optimization that involves trial and failure. [{$pagename}] is often necessary to modify data preprocessing and model parameters until the result achieves the desired properties.
Besides the term [{$pagename}], there are a number of terms with similar meanings, including automatic [classification], numerical [taxonomy], botryology (from Greek βότρυς "grape") and typological analysis. The subtle differences are often in the usage of the results: while in [data] mining, the resulting [classifications] are the matter of interest, in automatic [classification] the resulting discriminative power is of interest.
!! Category
%%category [Artificial Intelligence]%%
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
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* [#1] - [Cluster_analysis|Wikipedia:Cluster_analysis|target='_blank'] - based on information obtained 2017-11-25-
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop