module mlmodel._piecewise_tree_regression_common
#
Short summary#
module mlinsights.mlmodel._piecewise_tree_regression_common
Implements a custom criterion to train a decision tree.
Classes#
class |
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Common class to implement various version of mean square error. … |
Functions#
function |
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_test_criterion_check(Criterion criterion) |
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_test_criterion_impurity_improvement(Criterion criterion, double impurity_parent, double impurity_left, double impurity_right) … |
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_test_criterion_init(Criterion criterion, const DOUBLE_t[:, |
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_test_criterion_node_impurity(Criterion criterion) Test purposes. Methods cannot be directly called from python. |
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_test_criterion_node_impurity_children(Criterion criterion) Test purposes. Methods cannot be directly called from python. … |
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_test_criterion_node_value(Criterion criterion) Test purposes. Methods cannot be directly called from python. |
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_test_criterion_printf(Criterion crit) Test purposes. Methods cannot be directly called from python. |
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_test_criterion_proxy_impurity_improvement(Criterion criterion) Test purposes. Methods cannot be directly called from python. … |
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_test_criterion_update(Criterion criterion, SIZE_t new_pos) Test purposes. Methods cannot be directly called from python. … |
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assert_criterion_equal(Criterion c1, Criterion c2) |
Documentation#
@file @brief Implements a custom criterion to train a decision tree.
- class mlinsights.mlmodel._piecewise_tree_regression_common.CommonRegressorCriterion#
Bases:
Criterion
Common class to implement various version of mean square error. The code was inspired from hellinger_distance_criterion.pyx, Cython example of exposing C-computed arrays in Python without data copies, _criterion.pyx. This implementation is not efficient but was made that way on purpose. It adds the features to the class.
If the file does not compile, some explanations are given in :ref:`scikit-learn internal API <blog-internal-api-impurity-improvement>`_.
- __deepcopy__(self, memo=None)#
This does not a copy but mostly creates a new instance of the same criterion initialized with the same data.
- __getstate__(self)#
- __new__(**kwargs)#
- __pyx_vtable__ = <capsule object NULL>#
- __reduce_cython__(self)#
- __setstate__(self, d)#
- __setstate_cython__(self, __pyx_state)#
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_check(Criterion criterion)#
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_impurity_improvement(Criterion criterion, double impurity_parent, double impurity_left, double impurity_right)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_init(Criterion criterion, const DOUBLE_t[:, ::1] y, DOUBLE_t[:] sample_weight, double weighted_n_samples, SIZE_t[:] samples, SIZE_t start, SIZE_t end)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_node_impurity(Criterion criterion)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_node_impurity_children(Criterion criterion)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_node_value(Criterion criterion)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_printf(Criterion crit)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_proxy_impurity_improvement(Criterion criterion)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common._test_criterion_update(Criterion criterion, SIZE_t new_pos)#
Test purposes. Methods cannot be directly called from python.
- mlinsights.mlmodel._piecewise_tree_regression_common.assert_criterion_equal(Criterion c1, Criterion c2)#