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_doc/conf.py

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@@ -17,6 +17,7 @@
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"sphinx_issues",
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"matplotlib.sphinxext.plot_directive",
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"sphinx_runpython.blocdefs.sphinx_exref_extension",
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"sphinx_runpython.blocdefs.sphinx_faqref_extension",
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"sphinx_runpython.blocdefs.sphinx_mathdef_extension",
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"sphinx_runpython.docassert",
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"sphinx_runpython.epkg",

mlinsights/mlmodel/target_predictors.py

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@@ -30,16 +30,15 @@ class TransformedTargetRegressor2(BaseEstimator, RegressorMixin):
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Useful for applying a non-linear transformation in regression
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problems.
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:param regressor: object, `default=LinearRegression()`
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Parameters
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----------
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regressor : object, `default=LinearRegression()`
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Regressor object such as derived from ``RegressorMixin``. This
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regressor will automatically be cloned each time prior to fitting.
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:param transformer: str or object of type :class:`BaseReciprocalTransformer
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<mlinsights.mlmodel.sklearn_transform_inv.BaseReciprocalTransformer>`
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Attributes:
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* regressor_: object, fitted regressor.
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* transformer_: object, Transformer used in ``fit`` and ``predict``.
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transformer : str or object of type :class:`BaseReciprocalTransformer
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<mlinsights.mlmodel.sklearn_transform_inv.BaseReciprocalTransformer>`
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Examples
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--------
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print(tt.score(X, y))
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print(tt.regressor_.coef_)
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See notebook :ref:`l-sklearn-transformed-target` for a more complete example.
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See example :ref:`l-sklearn-transformed-target` for a more complete example.
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The class holds two attributes `regressor_`, the fitted regressor,
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`transformer_` transformer used in ``fit``, ``predict``,
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``decision_function``, ``predict_proba``.
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"""
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def __init__(self, regressor=None, transformer=None):
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Useful for applying permutation transformation in classification
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problems.
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:param classifier: object, default=LogisticRegression()
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Parameters
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----------
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classifier : object, default=LogisticRegression()
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Classifier object such as derived from ``ClassifierMixin``. This
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classifier will automatically be cloned each time prior to fitting.
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:param transformer: str or object of type :class:`BaseReciprocalTransformer
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transformer : str or object of type :class:`BaseReciprocalTransformer
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<mlinsights.mlmodel.sklearn_transform_inv.BaseReciprocalTransformer>`
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Transforms the features.
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Attributes:
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* classifier_ : object, Fitted classifier.
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* transformer_ : object Transformer used in ``fit``, ``predict``,
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``decision_function``, ``predict_proba``.
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Examples:
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.. runpython::
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print(tt.score(X, y))
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print(tt.classifier_.coef_)
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See notebook :ref:`l-sklearn-transformed-target` for a more complete example.
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See example :ref:`l-sklearn-transformed-target` for a more complete example.
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The class holds two attributes `classifier_`, the fitted classifier,
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`transformer_` transformer used in ``fit``, ``predict``,
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``decision_function``, ``predict_proba``.
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"""
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def __init__(self, classifier=None, transformer=None):

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