gpytorch.metrics¶
See the metrics tutorial for usage instructions.
- metrics.mean_absolute_error(test_y)¶
Mean Absolute Error.
- Parameters
pred_dist (MultivariateNormal) –
test_y (torch.Tensor) –
- metrics.mean_squared_error(test_y, squared=True)¶
Mean Squared Error.
- Parameters
pred_dist (MultivariateNormal) –
test_y (torch.Tensor) –
squared (bool) –
- metrics.mean_standardized_log_loss(test_y)¶
Mean Standardized Log Loss. Reference: Page No. 23, Gaussian Processes for Machine Learning, Carl Edward Rasmussen and Christopher K. I. Williams, The MIT Press, 2006. ISBN 0-262-18253-X
- Parameters
pred_dist (MultivariateNormal) –
test_y (torch.Tensor) –
- metrics.negative_log_predictive_density(test_y)¶
- Parameters
pred_dist (MultivariateNormal) –
test_y (torch.Tensor) –
- metrics.quantile_coverage_error(test_y, quantile=95.0)¶
Quantile coverage error.
- Parameters
pred_dist (MultivariateNormal) –
test_y (torch.Tensor) –
quantile (float) –