Class BinaryConfusionMatrix (2.24.1)

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

Confusion matrix for binary classification models. .. attribute:: positive_class_threshold

Threshold value used when computing each of the following metric.

:type: google.protobuf.wrappers_pb2.DoubleValue

Attributes

Name	Description
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.

builtins.object > proto.message.Message > BinaryConfusionMatrix

__delattr__(key)

Delete the value on the given field.

This is generally equivalent to setting a falsy value.

__eq__(other)

Return True if the messages are equal, False otherwise.

__ne__(other)

Return True if the messages are unequal, False otherwise.

__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.