Everyone is trying to make sense of, and extract value from, their data. In the real world, data is often not easy to separate, and patterns are not usually obvious. Clustering helps you find similarity groups in your data and it is one of the most common tasks in the Data Science; it provides analysts the ability to achieve better results for initiatives and understand customers and processes at a much deeper level than a human can achieve alone.
This visual uses a well known k-means clustering algorithm. You can control the algorithm parameters and the visual attributes to suit your needs.
NEW: support for tooltips on hover and selection
Here is how it works:
R package dependencies(auto-installed): nloptr, seriation, pbkrtest,NbClust, cluster, car, scales, fpc, mclust, apcluster, vegan
Supports R versions: R 3.3.1, R 3.3.0, MRO 3.3.1, MRO 3.3.0, MRO 3.2.2
This is an open source visual. Get the code from GitHub: https://github.com/microsoft/PowerBI-visuals-clustering-kmeans