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COMPONENTS OF CLUSTERING
Pattern representation – It refers to the number of classes, number of available patterns, the number, type and scale of the features available to the clustering algorithm.
DATA CLUSTERING TECHNIQUES
Data clustering can be done by two methods –
Hierarchical clustering
Partitonal clustering
1. Hierarchical clustering
Hierarchical clustering algorithm includes seven patterns three clusters of the given statistics data. Further it is classified into a dendogram representing the grouping of patterns and similarity levels at which the grouping change. It can be broken at different levels to provide different clustering’s of the data. This algorithm is further divided into-
2. Partitional Clustering
A partitional clustering algorithm obtains a single partition of the data instead of the clusters. A problem which accompanies the use of partitional algorithm is the choice of the number of desired output clusters. The algorithm is further divided into –
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