Package smile.deep.metric

package smile.deep.metric

Model validation metrics. A validation metric provides a quantitative measure of agreement between a predictive model and physical observations.

Related Packages

Package	Description
smile.deep	Deep learning.
smile.deep.activation	Activation functions.
smile.deep.layer	Neural network layers.
smile.deep.tensor	A tensor is a multidimensional array.

Class	Description
Accuracy	The accuracy is the proportion of true results (both true positives and true negatives) in the population.
Averaging	The averaging strategy to aggregate binary performance metrics across multi-classes.
Metric	The class metrics keeps track of metric states, which enables them to be able to calculate values through accumulations and synchronizations across multiple processes.
Precision	The precision or positive predictive value (PPV) is ratio of true positives to combined true and false positives, which is different from sensitivity.
Recall	Recall or true positive rate (TPR) (also called hit rate, sensitivity) is a statistical measures of the performance of a binary classification test.