Class ClusteringMetrics (2.2.0)

Version 2.2.0

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ClusteringMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Evaluation metrics for clustering models.

Attributes

Name	Description
davies_bouldin_index	`.wrappers.DoubleValue` Davies-Bouldin index.
mean_squared_distance	`.wrappers.DoubleValue` Mean of squared distances between each sample to its cluster centroid.
clusters	Sequence[`.gcb_model.Model.ClusteringMetrics.Cluster`] [Beta] Information for all clusters.

Inheritance

builtins.object > proto.message.Message > ClusteringMetrics

Classes

Cluster

Cluster(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Message containing the information about one cluster.

Methods

__delattr__

__delattr__(key)

Delete the value on the given field.

This is generally equivalent to setting a falsy value.

__eq__

__eq__(other)

Return True if the messages are equal, False otherwise.

__ne__

__ne__(other)

Return True if the messages are unequal, False otherwise.

__setattr__

__setattr__(key, value)

Set the value on the given field.

For well-known protocol buffer types which are marshalled, either the protocol buffer object or the Python equivalent is accepted.