An algorithm for the clustering of existing clusters is introduced in this paper. The algorithm was adopted from fuzzy-c-mean and modifications made to take into account the extra information, i.e. some data samples already form clusters. Partition coefficients, together with some other criteria, are used for testing cluster validity. The method was applied on Chinese character recognition and an encouraging result was obtained.link_to_subscribed_fulltex
The fuzzy clustering algorithm is to classify the data or indicators with a greater degree of simila...
The application of fuzzy cluster analysis to larger data sets can cause runtime and memory overflow ...
[[abstract]]Two well known fuzzy partition clustering algorithms, FCM and FPCM are based on Euclidea...
A hard partition clustering algorithm assigns equally distant points to one of the clusters, where e...
Abstract — Clustering is a collection of objects which are similar between them and dissimilar to th...
Clustering is widely used technique in data mining application for discovering patterns in large dat...
The cluster analysis of fuzzy clustering according to the fuzzy c-means algorithm has been described...
One of the shortcomings of the existing clustering methods is their problems dealing with different ...
Abstract: Cluster analysis is used for clustering a data set into groups of similar individuals. It ...
[[abstract]]The popular fuzzy c-means algorithm (FCM) is an objective function based clustering meth...
Clustering algorithms are an integral part of both computational intelligence and pattern recognitio...
Abstract:- The well known fuzzy partition clustering algorithms are most based on Euclidean distance...
Abstract—The algorithm of locally adaptive clustering for high dimensional data (LAC) processes soft...
In present time many clustering techniques are use the data mining. The clustering gives the best pe...
FOR CLUSTER ANALYSIS Abstract: Cluster analysis has been playing an important role in pattern recogn...
The fuzzy clustering algorithm is to classify the data or indicators with a greater degree of simila...
The application of fuzzy cluster analysis to larger data sets can cause runtime and memory overflow ...
[[abstract]]Two well known fuzzy partition clustering algorithms, FCM and FPCM are based on Euclidea...
A hard partition clustering algorithm assigns equally distant points to one of the clusters, where e...
Abstract — Clustering is a collection of objects which are similar between them and dissimilar to th...
Clustering is widely used technique in data mining application for discovering patterns in large dat...
The cluster analysis of fuzzy clustering according to the fuzzy c-means algorithm has been described...
One of the shortcomings of the existing clustering methods is their problems dealing with different ...
Abstract: Cluster analysis is used for clustering a data set into groups of similar individuals. It ...
[[abstract]]The popular fuzzy c-means algorithm (FCM) is an objective function based clustering meth...
Clustering algorithms are an integral part of both computational intelligence and pattern recognitio...
Abstract:- The well known fuzzy partition clustering algorithms are most based on Euclidean distance...
Abstract—The algorithm of locally adaptive clustering for high dimensional data (LAC) processes soft...
In present time many clustering techniques are use the data mining. The clustering gives the best pe...
FOR CLUSTER ANALYSIS Abstract: Cluster analysis has been playing an important role in pattern recogn...
The fuzzy clustering algorithm is to classify the data or indicators with a greater degree of simila...
The application of fuzzy cluster analysis to larger data sets can cause runtime and memory overflow ...
[[abstract]]Two well known fuzzy partition clustering algorithms, FCM and FPCM are based on Euclidea...