.. _example_model_selection_grid_search_digits.py: ============================================================ Parameter estimation using grid search with cross-validation ============================================================ This examples shows how a classifier is optimized by cross-validation, which is done using the :class:`sklearn.grid_search.GridSearchCV` object on a development set that comprises only half of the available labeled data. The performance of the selected hyper-parameters and trained model is then measured on a dedicated evaluation set that was not used during the model selection step. More details on tools available for model selection can be found in the sections on :ref:`cross_validation` and :ref:`grid_search`. **Python source code:** :download:`grid_search_digits.py ` .. literalinclude:: grid_search_digits.py :lines: 18-