H2O Clustering Evaluator

Evaluator for Clustering.

Output

It outputs the silhouette score

Type

ml-evaluator

Class

fire.nodes.h2o.NodeH2OClusteringEvaluator

Fields

Name	Title	Description
predictionCol	Prediction Column	The prediction column created during model scoringThe name of the column containing predictions generated by the clustering algorithm.
metric	Metric Column	The distance metric to use for evaluating the clustering algorithm. This can be set to ‘cosine’, ‘precomputed’, or another valid metric.
forceAllFinite	Force All Finite	Indicates whether to raise an error if any of the input data contains non-finite values.

Details

Node H2O Clustering Evaluator Details:

Evaluator for Clustering , which expects three input columns: prediction,metric and label.

Input Parameters

• OUTPUT STORAGE LEVEL : Keep this as DEFAULT.

• Prediction Column : The prediction column created during model scoringThe name of the column containing predictions generated by the clustering algorithm..

• Metric Column : The distance metric to use for evaluating the clustering algorithm. This can be set to ‘cosine’, ‘precomputed’, or another valid metric..

• Force All Finite : Indicates whether to raise an error if any of the input data contains non-finite values..