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BinaryConfusionMatrix(mapping=None, *, ignore_unknown_fields=False, **kwargs)
Confusion matrix for binary classification models.
Attributes
Name | Description |
positive_class_threshold |
`.wrappers.DoubleValue`
Threshold value used when computing each of the following metric. |
true_positives |
`.wrappers.Int64Value`
Number of true samples predicted as true. |
false_positives |
`.wrappers.Int64Value`
Number of false samples predicted as true. |
true_negatives |
`.wrappers.Int64Value`
Number of true samples predicted as false. |
false_negatives |
`.wrappers.Int64Value`
Number of false samples predicted as false. |
precision |
`.wrappers.DoubleValue`
The fraction of actual positive predictions that had positive actual labels. |
recall |
`.wrappers.DoubleValue`
The fraction of actual positive labels that were given a positive prediction. |
f1_score |
`.wrappers.DoubleValue`
The equally weighted average of recall and precision. |
accuracy |
`.wrappers.DoubleValue`
The fraction of predictions given the correct label. |
Inheritance
builtins.object > proto.message.Message > BinaryConfusionMatrixMethods
__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.