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Interface Summary | |
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ClusterMethod | A specification for clustering algorithms. |
EquivalenceClass | An equivalence class is a grouping of objects that are "similar". |
Partition | A Partition is a set of equivalence classes. |
Class Summary | |
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AbstractClusterMethod | A basic abstract implementation of clustering algorithms. |
ArrayListPartition | This partition class uses an ArrayList of LinkedListEquivalenceClasses to hold its equivalence classes. |
ClusteringTestClass | A test class (with a main() method) for clustering functionality. |
EquivalenceClassMember | A wrapper for an object and related data, where the object is a member of an equivalence class. |
KMedoidClustering | Performs k-medoid clustering, as follows:
TD(class) = sum(dist(p, case), all cases) TD = sum(TD(class), all classes) choose k prototypes assign remaining cases to nearest prototype Label A For each prototype p { Find the non-prot n for which TD is smallest when n is a protoype instead of p if the resulting TD is smaller than the TD without swapping { make n a prot instead of p reassign the other non-prots } } If you made it all the way through the loop without changing any prototypes, you're done otherwise goto A |
LinkedListEquivalenceClass | An equivalence class in which the members are maintained in a LinkedList. |
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