6.10.2.2.1. statsmodels.sandbox.tools.cross_val.KFold¶

class statsmodels.sandbox.tools.cross_val.KFold(n, k)[source]¶

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 = [[1, 2], [3, 4], [1, 2], [3, 4]]
>>> y = [1, 2, 3, 4]
>>> kf = cross_val.KFold(4, k=2)
>>> for train_index, test_index in kf:
...    print "TRAIN:", train_index, "TEST:", test_index
...    X_train, X_test, y_train, y_test = cross_val.split(train_index, test_index, X, y)
TRAIN: [False False  True  True] TEST: [ True  True False False]
TRAIN: [ True  True False False] TEST: [False False  True  True]

__init__(n, k)[source]¶