NbClust : An R Package for Determining the Relevant Number of Clusters in a Data Set
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Abstract
Clustering is the partitioning of a set of objects into groups (clusters) so that objects within a group are more similar to each others than objects in different groups. Most of the clustering algorithms depend on some assumptions in order to define the subgroups present in a data set. As a consequence, the resulting clustering scheme requires some sort of evaluation as regards its validity. The evaluation procedure has to tackle difficult problems such as the quality of clusters, the degree with which a clustering scheme fits a specific data set and the optimal number of clusters in a partitioning. In the literature, a wide variety of indices have been proposed to find the optimal number of clusters in a…
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Keywords
- Cluster analysis
- Set (abstract data type)
- Hierarchical clustering
- Data mining
- Computer science
- Correlation clustering
- Fuzzy clustering
- CURE data clustering algorithm
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