Module: tf.keras.metrics

Built-in metrics.

Classes

class AUC: Approximates the AUC (Area under the curve) of the ROC or PR curves.

class Accuracy: Calculates how often predictions equal labels.

class BinaryAccuracy: Calculates how often predictions match binary labels.

class BinaryCrossentropy: Computes the crossentropy metric between the labels and predictions.

class CategoricalAccuracy: Calculates how often predictions match one-hot labels.

class CategoricalCrossentropy: Computes the crossentropy metric between the labels and predictions.

class CategoricalHinge: Computes the categorical hinge metric between y_true and y_pred.

class CosineSimilarity: Computes the cosine similarity between the labels and predictions.

class FalseNegatives: Calculates the number of false negatives.