Class BinaryConfusionMatrix (3.26.0) 

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.