We can pick the number of clusters by varying it in a range of possible values and compute the silhouette score and the distorsion at every iteration. The optimal number is the one that maximizes the first and minimizes the second.distorsions = [] sil_scores = [] k_max = 80 for k ...
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compute: # specify a spark compute for monitoring job instance_type: standard_e4s_v3 runtime_version: "3.3" monitoring_target: ml_task: classification # model task type: [classification, regression, question_answering] endpoint_deployment_id: azureml:credit-default:main # azureml endpoint deployme...