ml.metrics #
fn absolute_error #
fn absolute_error[T](y &vtl.Tensor[T], y_true &vtl.Tensor[T]) !&vtl.Tensor[T]
fn accuracy_score #
fn accuracy_score[T](y_pred &vtl.Tensor[T], y_true &vtl.Tensor[T]) !f64
accuracy_score returns the proportion of correctly classified samples (as f64)
fn mean_absolute_error #
fn mean_absolute_error[T](y &vtl.Tensor[T], y_true &vtl.Tensor[T]) !T
fn mean_relative_error #
fn mean_relative_error[T](y &vtl.Tensor[T], y_true &vtl.Tensor[T]) !T
fn mean_squared_error #
fn mean_squared_error[T](y &vtl.Tensor[T], y_true &vtl.Tensor[T]) !T
fn relative_error #
fn relative_error[T](y &vtl.Tensor[T], y_true &vtl.Tensor[T]) !&vtl.Tensor[T]
fn squared_error #
fn squared_error[T](y &vtl.Tensor[T], y_true &vtl.Tensor[T]) !&vtl.Tensor[T]