GMM Clustering

Implements Gaussian Mixture Model clustering using Python Scikit-Learn. The configuration allows selection of columns containing numeric data for clustering, and the number of cluster to be generated.

The node includes a Conda Environment to install the required Python packages.

The node provides two outputs:
- Clustered Data: The original data plus a column 'Winner Cluster' indicating the cluster membership for that row.
- Statistics: AIC and BIC statistis showing the quality of the clustering.

Input ports

1. Type: Table
   Data
   Data to be clustered.

Output ports

1. Type: Table
   Clustered Data
   Clustered data with an additional column (Winner Cluster).
2. Type: Table
   Statistics
   Information statistics on cluster quality (AIC, BIC).