Detailed Description
A K-means clustering algorithm where every point has partial membership in each cluster. This algorithm is specified in Li, D. and Deogun, J. and Spaulding, W. and Shuart, B., Towards missing data imputation: A study of fuzzy K-means clustering method, In Rough Sets and Current Trends in Computing, Springer, pages 573–579, 2004.
#include <GCluster.h>
Public Member Functions | |
| GFuzzyKMeans (size_t nClusters, GRand *pRand) | |
| ~GFuzzyKMeans () | |
| GMatrix * | centroids () |
| Returns a k x d matrix, where each row is one of the k centroids. More... | |
| virtual void | cluster (const GMatrix *pData) |
| Performs clustering. More... | |
| void | init (const GMatrix *pData) |
| Selects random centroids and initializes internal data structures. More... | |
| void | recomputeCentroids (const GMatrix *pData) |
| Computes new centroids for each cluster. More... | |
| double | recomputeWeights (const GMatrix *pData) |
| Assigns each row to partial membership in each cluster, as measured with the dissimilarity metric. Returns the weighted-sum-distance of each row with the centroids. More... | |
| void | setFuzzifier (double d) |
| Specifies how fuzzy the membership in each cluster should be. d should be greater than 1, and is typically about 1.3. More... | |
| void | setReps (size_t r) |
| Specify the number of times to cluster the data. The best clustering (as measured by the weighted-sum-difference between each point with the centroids) will be kept. More... | |
| virtual size_t | whichCluster (size_t nVector) |
| Identifies the cluster of the specified row. More... | |
 Public Member Functions inherited from GClasses::GClusterer | |
| GClusterer (size_t nClusterCount) | |
| virtual | ~GClusterer () |
| size_t | clusterCount () |
| Return the number of clusters. More... | |
| virtual GMatrix * | reduce (const GMatrix &in) |
| Clusters pIn and outputs a dataset with one column that specifies the cluster number for each row. More... | |
| void | setMetric (GDistanceMetric *pMetric, bool own) |
| If own is true, then this object will delete pMetric when it is destroyed. More... | |
| Public Member Functions inherited from GClasses::GTransform | |
| GTransform () | |
| GTransform (const GDomNode *pNode) | |
| virtual | ~GTransform () |
Protected Member Functions | |
| bool | clusterAttempt (size_t nMaxIterations) |
| bool | selectSeeds (const GMatrix *pSeeds) |
| Protected Member Functions inherited from GClasses::GTransform | |
| virtual GDomNode * | baseDomNode (GDom *pDoc, const char *szClassName) const |
| Child classes should use this in their implementation of serialize. More... | |
Protected Attributes | |
| double | m_fuzzifier |
| GMatrix * | m_pCentroids |
| GRand * | m_pRand |
| GMatrix * | m_pWeights |
| size_t | m_reps |
| Protected Attributes inherited from GClasses::GClusterer | |
| size_t | m_clusterCount |
| bool | m_ownMetric |
| GDistanceMetric * | m_pMetric |
Constructor & Destructor Documentation
| GClasses::GFuzzyKMeans::GFuzzyKMeans | ( | size_t | nClusters, |
| GRand * | pRand | ||
| ) |
| GClasses::GFuzzyKMeans::~GFuzzyKMeans | ( | ) |
Member Function Documentation
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Returns a k x d matrix, where each row is one of the k centroids.
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Performs clustering.
Implements GClasses::GClusterer.
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| void GClasses::GFuzzyKMeans::init | ( | const GMatrix * | pData | ) |
Selects random centroids and initializes internal data structures.
| void GClasses::GFuzzyKMeans::recomputeCentroids | ( | const GMatrix * | pData | ) |
Computes new centroids for each cluster.
| double GClasses::GFuzzyKMeans::recomputeWeights | ( | const GMatrix * | pData | ) |
Assigns each row to partial membership in each cluster, as measured with the dissimilarity metric. Returns the weighted-sum-distance of each row with the centroids.
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Specifies how fuzzy the membership in each cluster should be. d should be greater than 1, and is typically about 1.3.
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Specify the number of times to cluster the data. The best clustering (as measured by the weighted-sum-difference between each point with the centroids) will be kept.
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virtual |
Identifies the cluster of the specified row.
Implements GClasses::GClusterer.
Member Data Documentation
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