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.

Options

Select columns containing data to be clustered
Clustering data must be numeric.
Number of clusters
Number of clusters generated by the gaussian mixture model

Input Ports

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Data to be clustered.

Output Ports

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Clustered data with an additional column (Winner Cluster).
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Information statistics on cluster quality (AIC, BIC).

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Extensions

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