mlquantify.evaluation.measures

process_inputs
absolute_error	Compute the absolute error for each class or a dictionary of errors if input is a dictionary.
mean_absolute_error	Compute the mean absolute error between the real and predicted prevalences.
kullback_leibler_divergence	Compute the Kullback-Leibler divergence between the real and predicted prevalences.
squared_error	Compute the mean squared error between the real and predicted prevalences.
mean_squared_error	Compute the mean squared error across all classes.
normalized_absolute_error	Compute the normalized absolute error between the real and predicted prevalences.
normalized_kullback_leibler_divergence	Compute the normalized Kullback-Leibler divergence between the real and predicted prevalences.
relative_absolute_error	Compute the relative absolute error between the real and predicted prevalences.
normalized_relative_absolute_error	Compute the normalized relative absolute error between the real and predicted prevalences.