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 and unzip the contents into your C:\Program Files\Sisense\PrismWeb\plugins\ folder. If the plugins folder doesn’t exist, just create it. After those files have been unzipped there, you may also have to restart the web server.
- 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.