7. Clustering

1. Click on Clustering under the Machine Learning category.

2. Model type: Select the type of Model you want to use.

   • KMeans / AgglomerativeClustering

   • GaussianMixture

   • DBSCAN

3. Allocate to: Specify the variable name to assign to the generated model.

4. Code view: Preview the generated code.

5. Run: Execute the code.

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KMeans / AgglomerativeClustering

1. N clusters: Specify the number of clusters to be generated.

2. Random state: Set the seed value for the random number generator.

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GaussianMixture

1. N components: Specify the number of Gaussian distributions to be used by the model to describe the data, determining how many clusters the data will be divided into.

2. Random state: Set the seed value for the random number generator.

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DBSCAN

1. Eps (Epsilon): Specify the maximum distance (radius) for forming clusters.

2. Min samples: Specify the minimum number of neighboring data points required for a point to be recognized as a cluster.