ezyrb.reducedordermodel.ReducedOrderModel.loo_error
- ReducedOrderModel.loo_error(*args, norm=<function norm>, **kwargs)[source]
Estimate the approximation error using leave-one-out strategy. The main idea is to create several reduced spaces by combining all the snapshots except one. The error vector is computed as the difference between the removed snapshot and the projection onto the properly reduced space. The procedure repeats for each snapshot in the database. The norm is applied on each vector of error to obtained a float number.
- Parameters:
norm (function) – the function used to assign at each vector of error a float number. It has to take as input a ‘numpy.ndarray` and returns a float. Default value is the L2 norm.
*args – additional parameters to pass to the fit method.
**kwargs – additional parameters to pass to the fit method.
- Returns:
the vector that contains the errors estimated for all parametric points.
- Return type: