nnmnkwii.metrics.mean_squared_error¶
-
nnmnkwii.metrics.
mean_squared_error
(X, Y, lengths=None)[source]¶ Mean squared error (MSE).
Parameters: - X (ndarray) – Input features, shape can be either of
(
D
,), (T x D
) or (B x T x D
). Both Numpy and torch arrays are supported. - Y (ndarray) – Target features, shape can be either of
(
D
,), (T x D
) or (B x T x D
). Both Numpy and torch arrays are supported. - lengths (list) – Lengths of padded inputs. This should only be specified if you give mini-batch inputs.
Returns: Mean squared error.
Return type: Tip
The function supports 3D padded inputs, while
sklearn.metrics.mean_squared_error()
doesn’t support.- X (ndarray) – Input features, shape can be either of
(