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Spearman Corr. Coef.¶

Module Interface¶

class torchmetrics.SpearmanCorrCoef(compute_on_step=None, **kwargs)[source]

where and are the rank associated to the variables and . Spearmans correlations coefficient corresponds to the standard pearsons correlation coefficient calculated on the rank variables.

Parameters

Example

>>> from torchmetrics import SpearmanCorrCoef
>>> target = torch.tensor([3, -0.5, 2, 7])
>>> preds = torch.tensor([2.5, 0.0, 2, 8])
>>> spearman = SpearmanCorrCoef()
>>> spearman(preds, target)
tensor(1.0000)


Initializes internal Module state, shared by both nn.Module and ScriptModule.

compute()[source]

Computes Spearman’s correlation coefficient.

Return type

Tensor

update(preds, target)[source]

Update state with predictions and targets.

Parameters
Return type

None

Functional Interface¶

torchmetrics.functional.spearman_corrcoef(preds, target)[source]

where and are the rank associated to the variables x and y. Spearmans correlations coefficient corresponds to the standard pearsons correlation coefficient calculated on the rank variables.

Parameters

Example

>>> from torchmetrics.functional import spearman_corrcoef
>>> target = torch.tensor([3, -0.5, 2, 7])
>>> preds = torch.tensor([2.5, 0.0, 2, 8])
>>> spearman_corrcoef(preds, target)
tensor(1.0000)

Return type

Tensor

© Copyright Copyright (c) 2020-2022, PyTorchLightning et al... Revision 45cc7044.

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