mindspore.train.F1

class mindspore.train.F1[source]

Calculates the F1 score. F1 is a special case of Fbeta when beta is 1. Refer to class mindspore.train.Fbeta for more details.

\[F_1=\frac{2\cdot true\_positive}{2\cdot true\_positive + false\_negative + false\_positive}\]

Supported Platforms:: Ascend GPU CPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor
>>> from mindspore.train import F1
>>>
>>> x = Tensor(np.array([[0.2, 0.5], [0.3, 0.1], [0.9, 0.6]]))
>>> y = Tensor(np.array([1, 0, 1]))
>>> metric = F1()
>>> metric.update(x, y)
>>> result = metric.eval()
>>> print(result)
[0.66666667 0.66666667]