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[MRG] DOC a note on data leakage and pipeline #9510

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[MRG] DOC a note on data leakage and pipeline #9510

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11 changes: 8 additions & 3 deletions doc/modules/pipeline.rst
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Expand Up @@ -16,11 +16,16 @@ into one. This is useful as there is often a fixed sequence
of steps in processing the data, for example feature selection, normalization
and classification. :class:`Pipeline` serves two purposes here:

**Convenience**: You only have to call ``fit`` and ``predict`` once on your
Convenience and encapsulation
You only have to call ``fit`` and ``predict`` once on your
data to fit a whole sequence of estimators.

**Joint parameter selection**: You can :ref:`grid search <grid_search>`
Joint parameter selection
You can :ref:`grid search <grid_search>`
over parameters of all estimators in the pipeline at once.
Safety
Pipelines help avoid leaking statistics from your test data into the
trained model in cross-validation, by ensuring that the same samples are
used to train the transformers and predictors.

All estimators in a pipeline, except the last one, must be transformers
(i.e. must have a ``transform`` method).
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