class sparse_ho.criterion.HeldOutLogistic(idx_train, idx_val)

Logistic loss on held out data

idx_train: ndarray

indices of the training set

idx_val: ndarray

indices of the validation set

__init__(idx_train, idx_val)

Initialize self. See help(type(self)) for accurate signature.


__init__(idx_train, idx_val)

Initialize self.

get_val(model, X, y, log_alpha[, monitor, tol])

Get value of criterion.

get_val_grad(model, X, y, log_alpha, …[, …])

Get value and gradient of criterion.

get_val_outer(X, y, mask, dense)

Compute the logistic loss on the validation set.

proj_hyperparam(model, X, y, log_alpha)

Project hyperparameter on a range of admissible values.