Clustering Application Benchmark

An application benchmark based on a set of clustering algorithms is described in this paper. The details of algorithms (K-means online, K-means batch, SOM-1 dimension, SOM-2 dimension, hierarchical K-means online and hierarchical SOM-1 dimension) are given. The code provided complies with ANSI C spe...

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Bibliographic Details
Main Authors: Altun, Oguz, Dursunoglu, Nilgun, Amasyali, M. Fatih
Format: Conference Proceeding
Language:English
Subjects:
Animals
Benchmark testing
Cities and towns
Clustering algorithms
Clustering Methods
Computer languages
Credit cards
Earthquakes
Plants (biology)
Self-organizing feature maps
Spatial databases
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Description
Summary:An application benchmark based on a set of clustering algorithms is described in this paper. The details of algorithms (K-means online, K-means batch, SOM-1 dimension, SOM-2 dimension, hierarchical K-means online and hierarchical SOM-1 dimension) are given. The code provided complies with ANSI C specifications, as a result is highly portable. The benchmark has been tested on various platforms using different compilers
DOI:10.1109/IISWC.2006.302742