module mlmodel.piecewise_tree_regression_criterion_fast#

Short summary#

module mlinsights.mlmodel.piecewise_tree_regression_criterion_fast

Implements a custom criterion to train a decision tree.

source on GitHub

Classes#

class

truncated documentation

SimpleRegressorCriterionFast

Criterion which computes the mean square error assuming points falling into one node are approximated by a constant. …

Documentation#

@file @brief Implements a custom criterion to train a decision tree.

class mlinsights.mlmodel.piecewise_tree_regression_criterion_fast.SimpleRegressorCriterionFast#

Bases: mlinsights.mlmodel._piecewise_tree_regression_common.CommonRegressorCriterion

Criterion which computes the mean square error assuming points falling into one node are approximated by a constant. The implementation follows the same design used in SimpleRegressorCriterion. This implementation is faster as it computes cumulated sums and avoids loops to compute intermediate gains.

__getstate__(self)#
__new__(**kwargs)#
__pyx_vtable__ = <capsule object NULL>#
__reduce_cython__(self)#
__setstate__(self, d)#
__setstate_cython__(self, __pyx_state)#