INNER CODE UNIT · Python
test_id
fabsig/GPBoost · python-package/gpboost/engine.py:463
test_id = [randidx[i: i + kstep] for i in range(0, num_data, kstep)]
train_id = [np.concatenate([test_id[i] for i in range(nfold) if k != i]) for k in range(nfold)]
folds = zip(train_id, test_id)
ret = CVBooster()
for train_idx, test_idx in folds:
if np.max(train_idx) >= num_data or np.max(test_idx) >= num_data:
raise ValueError("Index out of bound. "
"Maximum index in train_idx and test_idx should be less than num_data ({})"
.format(num_data))
if np.min(train_idx) < 0 or np.min(test_idx) < 0:
raise ValueError("Index out of bound. "
"Minimum index in train_idx and test_idx should be greater than or equal to 0")
train_set = full_data.subset(sorted(train_idx))
if full_data.free_raw_data:
valid_set = full_data.subset(sorted(test_idx))
else:
valid_set = full_data.subset(sorted(test_idx), reference=train_set)
# run preprocessing on the data set if needed