Metric resume

Documentation illustration (illustration unavailable in the archive).

In this section you’ll find a list of all metric fonctionalities.

  ICONS RESUME
Accuracy Documentation illustration (illustration unavailable in the archive). Calculates how often predictions equal labels.
BinaryAccuracy Documentation illustration (illustration unavailable in the archive). Calculates how often predictions match binary labels.
BinaryCrossentropy Documentation illustration (illustration unavailable in the archive). Computes the crossentropy metric between the labels and predictions.
BinaryIoU Documentation illustration (illustration unavailable in the archive). Computes the Intersection-Over-Union metric for class 0 and/or 1.
CategoricalAccuracy Documentation illustration (illustration unavailable in the archive). Calculates how often predictions match one-hot labels.
CategoricalCrossentropy Documentation illustration (illustration unavailable in the archive). Computes the crossentropy metric between the labels and predictions.
CategoricalHinge Documentation illustration (illustration unavailable in the archive). Computes the categorical hinge metric between y_true and y_pred.
CosineSimilarity Documentation illustration (illustration unavailable in the archive). Computes the cosine similarity between the labels and predictions.
FalseNegatives Documentation illustration (illustration unavailable in the archive). Calculates the number of false negatives.
FalsePositives Documentation illustration (illustration unavailable in the archive). Calculates the number of false positives.
Hinge Documentation illustration (illustration unavailable in the archive). Computes the hinge metric between y_true and y_pred.
Huber Documentation illustration (illustration unavailable in the archive). Computes the huber metrics between y_true and y_pred.
IoU Documentation illustration (illustration unavailable in the archive). Computes the Intersection-Over-Union metric for specific target classes.
KLDivergence Documentation illustration (illustration unavailable in the archive). Computes Kullback-Leibler divergence metric between y_true and y_pred.
LogCoshError Documentation illustration (illustration unavailable in the archive). Computes the logarithm of the hyperbolic cosine of the prediction error.
Mean Documentation illustration (illustration unavailable in the archive). Computes the mean of the given values.
MeanAbsoluteError Documentation illustration (illustration unavailable in the archive). Computes the mean absolute error between the labels and predictions.
MeanAbsolutePercentageError Documentation illustration (illustration unavailable in the archive). Computes the mean absolute percentage error between y_true and y_pred.
MeanIoU Documentation illustration (illustration unavailable in the archive). Computes the mean Intersection-Over-Union metric.
MeanRelativeError Documentation illustration (illustration unavailable in the archive). Computes the mean relative error by normalizing with the given values.
MeanSquaredError Documentation illustration (illustration unavailable in the archive). Computes the mean squared error between y_true and y_pred.
MeanSquaredLogarithmicError Documentation illustration (illustration unavailable in the archive). Computes the mean squared logarithmic error between y_true and y_pred.
MeanTensor Documentation illustration (illustration unavailable in the archive). Computes the element-wise mean of the given tensors.
OneHotIoU Documentation illustration (illustration unavailable in the archive). Computes the Intersection-Over-Union metric for one-hot encoded labels.
OneHotMeanIoU Documentation illustration (illustration unavailable in the archive). Computes mean Intersection-Over-Union metric for one-hot encoded labels.
Poisson Documentation illustration (illustration unavailable in the archive). Computes the poisson metric between y_true and y_pred.
Precision Documentation illustration (illustration unavailable in the archive). Computes the precision of the predictions with respect to the labels.
PrecisionAtRecall Documentation illustration (illustration unavailable in the archive). Computes best precision where recall is > specified value.
Recall Documentation illustration (illustration unavailable in the archive). Computes the recall of the predictions with respect to the labels.
RecallAtPrecision Documentation illustration (illustration unavailable in the archive). Computes best recall where precision is > specified value.
RootMeanSquaredError Documentation illustration (illustration unavailable in the archive). Computes root mean squared error metric between y_true and y_pred.
SensitivityAtSpecificity Documentation illustration (illustration unavailable in the archive). Computes best sensitivity where specificity is > specified value.
SparseCategoricalAccuracy Documentation illustration (illustration unavailable in the archive). Calculates how often predictions match integer labels.
SparseCategoricalCrossentropy Documentation illustration (illustration unavailable in the archive). Computes the crossentropy metric between the labels and predictions.
SparseTopKCategoricalAccuracy Documentation illustration (illustration unavailable in the archive). Computes how often integer targets are in the top K predictions.
Specificity Documentation illustration (illustration unavailable in the archive). Computes the specificity of the predictions with respect to the labels.
SpecificityAtSensitivity Documentation illustration (illustration unavailable in the archive). Computes best specificity where sensitivity is > specified value.
SquaredHinge Documentation illustration (illustration unavailable in the archive). Computes the squared hinge metric between y_true and y_pred.
Sum Documentation illustration (illustration unavailable in the archive). Computes the sum of the given values.
TopKCategoricalAccuracy Documentation illustration (illustration unavailable in the archive). Computes how often targets are in the top K predictions.
TrueNegatives Documentation illustration (illustration unavailable in the archive). Calculates the number of true negatives.
TruePositives Documentation illustration (illustration unavailable in the archive). Calculates the number of true positives.