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Compare clusters is a tool to identify the optimal number of clusters for K-means clusteringClustering using the Davies-Bouldin index. The Davies-Bouldin index is a measure of cluster quality where a lower value indicates more optimal better clustering, i.e., the separation between points within the clusters is low (tight clusters) and separation between clusters is high (distinct clusters). 

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• Click a point on the plot to select it or type the number of clusters in the text box Partition data into      clusters

Selecting a point sets it as the number of clusters to partition the data into. The number of clusters with the lowest Davies-Bouldin index value is chosen by default. 

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A K-means clustering task node and a Clustering result data node are produced. Please see our documentation on K-means clusteringClustering for more details.

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