Typical workflow for k-means clustering - 5.2 English - 68552

Initialize a aoclda.clustering.kmeans() object with options set in the class constructor.

Compute the k-means clusters using aoclda.clustering.kmeans.fit().

Perform further transformations or predictions using aoclda.clustering.kmeans.transform() or aoclda.clustering.kmeans.predict().

Extract results from the aoclda.clustering.kmeans() object via its class attributes.

Initialize a da_handle with da_handle_type da_handle_kmeans.

Set the number of clusters required and other options using da_options_set_? (see below).

Pass data to the handle using da_kmeans_set_data_?.

Optionally set the initial centres using da_kmeans_set_init_centres_?.

Compute the k-means clusters using da_kmeans_compute_?.

Perform further computations as required, using da_kmeans_transform_? or da_kmeans_predict_?.

Extract results using da_handle_get_result_?.