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Commit dbaea6f1 authored by Olivier Grisel's avatar Olivier Grisel
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typo

parent 159bcb1d
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......@@ -59,13 +59,13 @@ Scipy sparse CSR matrices are used for ``X`` and numpy arrays are used for ``y``
You may load a dataset like this::
>>> from scikits.learn.datasets import load_svmlight_format
>>> X_train, y_train = load_svmlight_format("/path/to/train_dataset.txt")
>>> from scikits.learn.datasets import load_svmlight_file
>>> X_train, y_train = load_svmlight_file("/path/to/train_dataset.txt")
... # doctest: +SKIP
You may also load two datasets at once::
>>> X_train, y_train, X_test, y_test = load_svmlight_format(
>>> X_train, y_train, X_test, y_test = load_svmlight_file(
... "/path/to/train_dataset.txt",
... "/path/to/test_dataset.txt") # doctest: +SKIP
......@@ -73,7 +73,7 @@ In this case, ``X_train`` and ``X_test`` are guaranteed to have the same number
of features. Another way to achieve the same result is to fix the number of
features::
>>> X_test, y_test = load_svmlight_format(
>>> X_test, y_test = load_svmlight_file(
... "/path/to/test_dataset.txt", n_features=X_train.shape[1])
... # doctest: +SKIP
......
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