scikit-learn/doc/modules/grid_search.rst

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Grid Search
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.. currentmodule:: sklearn.grid_search
Grid Search is used to optimize the parameters of a model
(e.g. Support Vector Classifier, Lasso, etc.) using cross-validation.
Main class is :class:`GridSearchCV`.
Examples
--------
See :ref:`example_grid_search_digits.py` for an example of
Grid Search computation on the digits dataset.
See :ref:`example_grid_search_text_feature_extraction.py` for an example
of Grid Search coupling parameters from a text documents feature extractor
(n-gram count vectorizer and TF-IDF transformer) with a classifier
(here a linear SVM trained with SGD with either elastic net or L2 penalty).
Notes
-----
Computations can be run in parallel if your OS supports it, by using
the keyword n_jobs=-1, see function signature for more details.