6.11.5. scikits.learn.cross_val.LeaveOneLabelOut¶
- class scikits.learn.cross_val.LeaveOneLabelOut(labels)¶
Leave-One-Label_Out cross-validation iterator
Provides train/test indexes to split data in train test sets
- __init__(labels)¶
Leave-One-Label_Out cross validation
Provides train/test indexes to split data in train test sets
Parameters : labels : list
List of labels
Examples
>>> from scikits.learn import cross_val >>> X = np.array([[1, 2], [3, 4], [5, 6], [7, 8]]) >>> y = np.array([1, 2, 1, 2]) >>> labels = np.array([1, 1, 2, 2]) >>> lol = cross_val.LeaveOneLabelOut(labels) >>> len(lol) 2 >>> print lol scikits.learn.cross_val.LeaveOneLabelOut(labels=[1 1 2 2]) >>> for train_index, test_index in lol: ... 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] ... print X_train, X_test, y_train, y_test TRAIN: [False False True True] TEST: [ True True False False] [[5 6] [7 8]] [[1 2] [3 4]] [1 2] [1 2] TRAIN: [ True True False False] TEST: [False False True True] [[1 2] [3 4]] [[5 6] [7 8]] [1 2] [1 2]