FLAME clustering: Difference between revisions

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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 membershipsmembership]]s:

## Initialization of fuzzy membership:

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