module `mlmodel.sklearn_testing`#

Short summary#

module mlinsights.mlmodel.sklearn_testing

Helpers to test a model which follows scikit-learn API.

Functions#

function	truncated documentation
`_assert_dict_equal`
`_assert_list_equal`
`_assert_tuple_equal`
`_get_test_instance`
`assert_estimator_equal`	Checks that two models are equal.
`clone_with_fitted_parameters`	Clones an estimator with the fitted results.
`test_sklearn_clone`	Tests that a cloned model is similar to the original one.
`test_sklearn_grid_search_cv`	Creates a model, checks that a grid search works with it.
`test_sklearn_pickle`	Creates a model, fit, predict and check the prediction are similar after the model was pickled, unpickled.
`train_test_split_with_none`	Splits into train and test data even if they are None.

Documentation#

Helpers to test a model which follows scikit-learn API.

source on GitHub

mlinsights.mlmodel.sklearn_testing._assert_dict_equal(a, b, ext)#

mlinsights.mlmodel.sklearn_testing._assert_list_equal(l1, l2, ext)#

mlinsights.mlmodel.sklearn_testing._assert_tuple_equal(t1, t2, ext)#

mlinsights.mlmodel.sklearn_testing._get_test_instance()#

mlinsights.mlmodel.sklearn_testing.assert_estimator_equal(esta, estb, ext=None)#

Checks that two models are equal.

Parameters:

esta – first estimator
estb – second estimator
ext – unit test class

The function raises an exception if the comparison fails.

source on GitHub

mlinsights.mlmodel.sklearn_testing.clone_with_fitted_parameters(est)#

Clones an estimator with the fitted results.

Parameters:: est – estimator
Returns:: cloned object

source on GitHub

mlinsights.mlmodel.sklearn_testing.test_sklearn_clone(fct_model, ext=None, copy_fitted=False)#

Tests that a cloned model is similar to the original one.

Parameters:

fct_model – function which creates the model
ext – unit test class instance
copy_fitted – copy fitted parameters as well

Returns:

model, cloned model

Raises:

AssertionError

source on GitHub

mlinsights.mlmodel.sklearn_testing.test_sklearn_grid_search_cv(fct_model, X, y=None, sample_weight=None, **grid_params)#

Creates a model, checks that a grid search works with it.

Parameters:

fct_model – function which creates the model
X – X
y – y
sample_weight – sample weight
grid_params – parameter to use to run the grid search.

Returns:

dictionary with results

Raises:

AssertionError

source on GitHub

mlinsights.mlmodel.sklearn_testing.test_sklearn_pickle(fct_model, X, y=None, sample_weight=None, **kwargs)#

Creates a model, fit, predict and check the prediction are similar after the model was pickled, unpickled.

Parameters:

fct_model – function which creates the model
X – X
y – y
sample_weight – sample weight
kwargs – additional parameters for numpy.testing.assert_almost_equal

Returns:

model, unpickled model

Raises:

AssertionError

source on GitHub

mlinsights.mlmodel.sklearn_testing.train_test_split_with_none(X, y=None, sample_weight=None, random_state=0)#

Splits into train and test data even if they are None.

Parameters:

X – X
y – y
sample_weight – sample weight
random_state – random state

Returns:

source on GitHub

module mlmodel.sklearn_testing#

Short summary#

Functions#

Documentation#

module `mlmodel.sklearn_testing`#