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latest version v1.9 - last update 24 Nov 2005 |
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#include <ltiCompetitiveAgglomeration.h>
Inheritance diagram for lti::competitiveAgglomeration:


Public Member Functions | |
| competitiveAgglomeration () | |
| competitiveAgglomeration (const parameters &par) | |
| competitiveAgglomeration (const competitiveAgglomeration &other) | |
| virtual | ~competitiveAgglomeration () |
| virtual const char * | getTypeName () const |
| competitiveAgglomeration & | copy (const competitiveAgglomeration &other) |
| competitiveAgglomeration & | operator= (const competitiveAgglomeration &other) |
| virtual classifier * | clone () const |
| const parameters & | getParameters () const |
| bool | train (const lti::dmatrix &input) |
| bool | train (const lti::dmatrix &input, ivector &ids) |
Classes | |
| class | parameters |
| The parameters for the class competitiveAgglomeration. More... | |
30, No. 7, pp. 1109-1119, 1997. The algorithm is a fuzzy clustering algorithm, which reduces a given partition to an optimal number of clusters. Here, the initial partition is generated by first performing a fuzzy-C-Means run on the data. Note: since the number of clusters will only be decreased by this algorithm, the fuzzy-C-Means parameters should be modified such that the number of clusters is chosen to be much larger than the expected number of clusters.
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Default constructor.
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Construct a classifier using the given parameters.
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Copy constructor.
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Destructor.
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Returns a pointer to a clone of this classifier.
Implements lti::classifier. |
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Copy data of "other" classifier.
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Returns used parameters.
Reimplemented from lti::centroidClustering. |
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Returns the name of this type ("competitiveAgglomeration").
Reimplemented from lti::centroidClustering. |
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Alias for copy member.
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calls centroidClustering::train
Reimplemented from lti::centroidClustering. |
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train clusters from given data.
Implements lti::centroidClustering. |