K-Means Clustering

By Sisense

Widgets

Add-on Version 1.0.1

OS Support

Windows

Linux

Supported Sisense Versions (Linux) 8.0.0 - Latest

Last Updated November 21, 2023

Tags

chart

cluster

HIPAA

R-integration

statistical

Visualization

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This add-on is pre-installed on Sisense in Linux environments and its version could be different. The download link is for Sisense on Windows.

The K-means add-on enables you to perform K-Means clustering on your data within the Sisense Web Application.

K-means clusters are partitioned into statistically significant groups according to measures you define by the k-means method.

The K-means add-on requires that you have an R server installed and it is configured to work with Sisense. For more information, see Connecting Sisense to your R Server.

Through the K-Means add-on, you can identify distinct groups in your data based on how close they are to each other.

To install the K-means add-on:

Download the attachment.
Extract the .zip folder into the plugins folder. If the folder does not exist, create it prior to extracting the .zip file.
For V7.1 and earlier: C:Program FilesSisensePrismWebplugins
For V7.2 and later: C:Program FilesSisenseappplugins
In the Sisense Web Application, create a scatter chart by selecting New Widget > Advanced Configuration > Scatter Chart.
Define the relevant measures for your scatter chart.
From the widget menu, select K-means.

The Clustering window is displayed.
In the Clustering window, add up to four measures. Measures represent numeric matrices of data, or an object that can be coerced to such a matrix (such as a numeric vector or a data frame with all numeric columns).
Select the number of clusters. For each cluster, Sisense assigns a color to represent the cluster as a statistically significant group within the chart.
Click Apply, then click Apply in the Widget Editor. The k-means clustering widget is displayed in the dashboard.