About Clustering Models

A clustering model is an unsupervised learning algorithm 

a clustering problem you will try to group together similar objects or similar attributes. For example you want to detect similar regime of operation in production process (the clustering will group together records in time that looks more or less the same) or you want to find clusters of attributes that have similar behavior.

K-Means

K-means clustering is a method which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest  mean. This results in a partitioning of the data space into Voronio cells.

To launch the regression visualization tool, select Models > K-Means from the menu. Alternatively, click the corresponding icon in the sidebar.

Create a K-Means

The parameters for a curve are defined on two tabs at the top of the page: Data and Properties.

On the Data tab: 

1. Select a Data source from the list.
2. Select an Object set from the list.
3. ... 

Control the View

Use the control menu below the chart to modify the zoom, set rulers, apply new object sets and export. See [x-ref] for more information.