reservoirpy.observables.mse

reservoirpy.observables.mse(y_true, y_pred)

Mean squared error metric:

\[\frac{\sum_{i=0}^{N-1} (y_i - \hat{y}_i)^2}{N}\]

Parameters:

• y_true (array-like of shape (N, features)) – Ground truth values.

• y_pred (array-like of shape (N, features)) – Predicted values.

Returns:

Mean squared error.

Return type:

float