Module: tfma.post_export_metrics

Stay organized with collections Save and categorize content based on your preferences.

Library containing helpers for adding post export metrics for evaluation.

These post export metrics can be included in the add_post_export_metrics parameter of Evaluate to compute them.

Functions

auc(...): This is the function that the user calls.

auc_plots(...): This is the function that the user calls.

calibration(...): This is the function that the user calls.

calibration_plot_and_prediction_histogram(...): This is the function that the user calls.

confusion_matrix_at_thresholds(...): This is the function that the user calls.

example_count(...): This is the function that the user calls.

example_weight(...): This is the function that the user calls.

fairness_auc(...): This is the function that the user calls.

fairness_indicators(...): This is the function that the user calls.

mean_absolute_error(...): This is the function that the user calls.

mean_squared_error(...): This is the function that the user calls.

precision_at_k(...): This is the function that the user calls.

recall_at_k(...): This is the function that the user calls.

root_mean_squared_error(...): This is the function that the user calls.

squared_pearson_correlation(...): This is the function that the user calls.

DEFAULT_KEY_PREFERENCE ('logistic', 'predictions', 'probabilities', 'logits')