# 7. Clustering

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1. Click on ***Clustering*** under the ***Machine Learning*** category.

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2. ***Model type***: Select the type of Model you want to use.
   * [KMeans / AgglomerativeClustering](#kmeans-agglomerativeclustering)
   * [GaussianMixture](#gaussianmixture)
   * [DBSCAN](#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

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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

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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

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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.