Clustering with outliers (DBSCAN)
12-05-2016 01:11 AM - last edited 12-12-2016 07:52 AM
12-05-2016 01:11 AM - edited 12-12-2016 07:52 AM
Clustering enables you to find similarity groups in your data, using the well-known density-based spatial clustering of applications with noise (DBSCAN). Unlike many other clustering algorithms, DBSCAN also finds outliers. Settings for the visual let you control and refine algorithm parameters to meet your needs.
Service prerequisites: This R-powered custom visual is used without any modifications in the Power BI service
Desktop prerequisites: To run R scripts in Power BI Desktop, you must separately install R on your local computer.
You can download and install R for free from the Revolution Open download page or the CRAN Repository. For more information, see this article.
R package dependencies (see attached script for int): scales, fpc, car, dbscan
Supports R versions: R 3.3.2, R 3.3.1, R 3.3.0, MRO 3.3.2, MRO 3.3.1, MRO 3.3.0