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