6.11.3. scikits.learn.cross_val.KFold

class scikits.learn.cross_val.KFold(n, k)

K-Folds cross validation iterator

Provides train/test indexes to split data in train test sets

__init__(n, k)

K-Folds cross validation iterator

Provides train/test indexes to split data in train test sets

Parameters :

n: int :

Total number of elements

k: int :

number of folds

Notes

All the folds have size trunc(n/k), the last one has the complementary

Examples

>>> from scikits.learn import cross_val
>>> X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
>>> y = np.array([1, 2, 3, 4])
>>> kf = cross_val.KFold(4, k=2)
>>> len(kf)
2
>>> print kf
scikits.learn.cross_val.KFold(n=4, k=2)
>>> for train_index, test_index in kf:
...    print "TRAIN:", train_index, "TEST:", test_index
...    X_train, X_test = X[train_index], X[test_index]
...    y_train, y_test = y[train_index], y[test_index]
TRAIN: [False False  True  True] TEST: [ True  True False False]
TRAIN: [ True  True False False] TEST: [False False  True  True]