2-D Projection of Clustered Data

This component perfoms k-means clustering on the input data and then reduce the clustered data to 2 dimensions using PCA. Additionally, the 2D data are color endcoded based on the cluster they are contained in. Finally they are visualized using a scatter plot.

The number of clusters for K-Means and the maximum number of iterations can be set via the component dialog box. The default values for K and maximum iterations are 2 and 99 respectively .

This component works with any input data with at least 2 columns of type double with values between the range of 0 and 1.

Input ports

1. Type: Table
   0
   Input data to the component.