Class BinaryConfusionMatrix (3.25.0)

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

Confusion matrix for binary classification models.

Attributes
Name	Description
positive_class_threshold	google.protobuf.wrappers_pb2.DoubleValue Threshold value used when computing each of the following metric.
true_positives	google.protobuf.wrappers_pb2.Int64Value Number of true samples predicted as true.
false_positives	google.protobuf.wrappers_pb2.Int64Value Number of false samples predicted as true.
true_negatives	google.protobuf.wrappers_pb2.Int64Value Number of true samples predicted as false.
false_negatives	google.protobuf.wrappers_pb2.Int64Value Number of false samples predicted as false.
precision	google.protobuf.wrappers_pb2.DoubleValue The fraction of actual positive predictions that had positive actual labels.
recall	google.protobuf.wrappers_pb2.DoubleValue The fraction of actual positive labels that were given a positive prediction.
f1_score	google.protobuf.wrappers_pb2.DoubleValue The equally weighted average of recall and precision.
accuracy	google.protobuf.wrappers_pb2.DoubleValue The fraction of predictions given the correct label.

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.