# Compare Clusters ## What is Compare clusters? Compare clusters is a tool to identify the optimal number of clusters for K-means Clustering using the Davies-Bouldin index. The Davies-Bouldin index is a measure of cluster quality where a lower value indicates better clustering, i.e., the separation between points within the clusters is low (tight clusters) and separation between clusters is high (distinct clusters). ## Running Compare clusters We recommend normalizing your data prior to running *Compare clusters*, but the task will run on any counts data node. * Click the counts data node * Click the **Exploratory analysis** section of the toolbox * Click **Compare clusters** * Configure the parameters * Click **Finish** to run (Figure 1)

Figure 1. Compare clusters configuration dialog

The parameters for *Compare clusters* are the same as for *K-means* *clustering*. ## Compare clusters task report The *Compare clusters* task report is an interactive line chart with the number of clusters on the x-axis and the Davies-Bouldin index on the y-axis (Figure 2).

Figure 2. The Compare clusters task report shows the Davies-Bouldin index for each number of clusters.

The *Compare clusters* task report can be used to run *K-means clustering.* * 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. * Click **Generate clusters** to run *K-means clustering* with the selected number of clusters A *K-means clustering* task node and a *Clustering result* data node are produced. Please see our documentation on K-means Clustering for more details. ## Additional Assistance If you need additional assistance, please visit our support page to submit a help ticket or find phone numbers for regional support.