K-Means Clustering

By:
Sisense
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:

  1. Download the attachment.
  2. 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 Files\Sisense\PrismWeb\plugins
    For V7.2 and later
    : C:\Program Files\Sisense\app\plugins
  3. In the Sisense Web Application, create a scatter chart by selecting New Widget > Advanced Configuration > Scatter Chart.
  4. Define the relevant measures for your scatter chart.
  5. From the widget menu, select K-means.

    The Clustering window is displayed.
  6. 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).
  7. Select the number of clusters. For each cluster, Sisense assigns a color to represent the cluster as a statistically significant group within the chart.
  8. Click Apply, then click Apply in the Widget Editor. The k-means clustering widget is displayed in the dashboard.
This is a free add-on, click here to get it now.
  • Category:
    • Widgets
  • Last Updated
    6 months ago
  • Earliest Supported Version
    6.7
  • Latest Supported Version
    7.2
  • Tags
    • chart
    • cluster
    • R-integration
    • statistical
    • visualization