L1Loss#
- class L1Loss[ソース]#
ベースクラス:
Loss
This class computes the L1 loss (i.e. absolute error) for each sample as:
\[\text{L1Loss}(predict, target) = \sum_{i=0}^{N_{\text{elements}}} \left| predict_i - target_i \right|.\]Methods
- evaluate(predict, target)[ソース]#
An abstract method for evaluating the loss function. Inputs are expected in a shape of
(N, *)
. WhereN
is a number of samples. Loss is computed for each sample individually.- パラメータ:
- 戻り値:
An array with values of the loss function of the shape
(N, 1)
.- 例外:
QiskitMachineLearningError – shapes of predict and target do not match
- 戻り値の型:
- gradient(predict, target)[ソース]#
An abstract method for computing the gradient. Inputs are expected in a shape of
(N, *)
. WhereN
is a number of samples. Gradient is computed for each sample individually.- パラメータ:
- 戻り値:
An array with gradient values of the shape
(N, *)
. The output shape depends on the loss function.- 例外:
QiskitMachineLearningError – shapes of predict and target do not match.
- 戻り値の型: