FLAME clustering: Difference between revisions

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{{Short description|Type of algorithm for data clustering}}

'''Fuzzy clustering by Local Approximation of MEmberships (FLAME)''' is a [[data clustering]] algorithm that defines clusters in the dense parts of a dataset and performs cluster assignment solely based on the neighborhood relationships among objects. The key feature of this algorithm is that, the neighborhood relationships among neighboring objects in the feature space are used to constrain the memberships of neighboring objects in the fuzzy membership space.

{{COI|date=August 2010}}

'''Fuzzy clustering by Local Approximation of MEmberships (FLAME)''' is a [[data clustering]] algorithm that defines clusters in the dense parts of a dataset and performs cluster assignment solely based on the neighborhood relationships among objects. The key feature of this algorithm is that, the neighborhood relationships among neighboring objects in the [[feature space]] are used to constrain the memberships of neighboring objects in the fuzzy membership space.

==Description of the FLAME algorithm==

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### Cluster Outliers: object with density lower than all its neighbors, and lower than a predefined threshold;

### the rest.

# Local/Neighborhood approximation of [[fuzzy membershipsmembership]]s:

## Initialization of fuzzy membership:

### Each CSO is assigned with fixed and full membership to itself to represent one cluster;

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==External links==

* [http://www.biomedcentral.com/1471-2105/8/3 BMC Bioinformatics (2007): FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data]

* [https://web.archive.org/web/20080622172700/http://flame-clustering.googlecode.com/svn/trunk/ FLAME source codes in C released under FreeBSD-like license on GoogleCode]

{{DEFAULTSORT:Flame Clustering}}

[[Category:Data clustering algorithms]]

[[Category:StatisticalCluster analysis algorithms]]

[[Category:Data mining]]

[[Category:Machine learning]]