ml_clustering_evaluator

From sparklyr v0.8.0 by Javier Luraschi

Spark ML - Clustering Evaluator

Evaluator for clustering results. The metric computes the Silhouette measure using the squared Euclidean distance. The Silhouette is a measure for the validation of the consistency within clusters. It ranges between 1 and -1, where a value close to 1 means that the points in a cluster are close to the other points in the same cluster and far from the points of the other clusters.

Usage

ml_clustering_evaluator(x, features_col = "features",
  prediction_col = "prediction", metric_name = "silhouette",
  uid = random_string("clustering_evaluator_"), ...)

Arguments

x: A spark_connection object or a tbl_spark containing label and prediction columns. The latter should be the output of sdf_predict.
features_col: Name of features column.
prediction_col: Name of the prediction column.
metric_name: The performance metric. Currently supports "silhouette".
uid: A character string used to uniquely identify the ML estimator.
...: Optional arguments; currently unused.

Value

The calculated performance metric

Documentation reproduced from package sparklyr, version 0.8.0, License: Apache License 2.0 | file LICENSE

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