8000 Use RealNotInt for parameters that accept ints and floats · sebp/scikit-survival@0e9ca7e · GitHub
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Use RealNotInt for parameters that accept ints and floats
See scikit-learn/scikit-learn#25797
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‎sksurv/tree/tree.py

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,7 @@
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from sklearn.tree._splitter import Splitter
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from sklearn.tree._tree import BestFirstTreeBuilder, DepthFirstTreeBuilder, Tree
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from sklearn.tree._utils import _any_isnan_axis0
12-
from sklearn.utils._param_validation import Interval, StrOptions
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from sklearn.utils._param_validation import Interval, RealNotInt, StrOptions
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from sklearn.utils.validation import (
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_assert_all_finite_element_wise,
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_check_n_features,
@@ -161,16 +161,16 @@ class SurvivalTree(BaseEstimator, SurvivalAnalysisMixin):
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"max_depth": [Interval(Integral, 1, None, closed="left"), None],
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"min_samples_split": [
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Interval(Integral, 2, None, closed="left"),
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Interval(Real, 0.0, 1.0, closed="neither"),
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Interval(RealNotInt, 0.0, 1.0, closed="neither"),
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],
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"min_samples_leaf": [
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Interval(Integral, 1, None, closed="left"),
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Interval(Real, 0.0, 0.5, closed="right"),
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Interval(RealNotInt, 0.0, 0.5, closed="right"),
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],
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"min_weight_fraction_leaf": [Interval(Real, 0.0, 0.5, closed="both")],
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"max_features": [
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Interval(Integral, 1, None, closed="left"),
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Interval(Real, 0.0, 1.0, closed="right"),
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Interval(RealNotInt, 0.0, 1.0, closed="right"),
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StrOptions({"sqrt", "log2"}),
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None,
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],
@@ -363,7 +363,7 @@ def _check_params(self, n_samples):
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max_leaf_nodes = -1 if self.max_leaf_nodes is None else self.max_leaf_nodes
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366-
if isinstance(self.min_samples_leaf, (Integral, np.integer)):
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if isinstance(self.min_samples_leaf, Integral):
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min_samples_leaf = self.min_samples_leaf
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else: # float
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min_samples_leaf = int(ceil(self.min_samples_leaf * n_samples))
@@ -397,7 +397,7 @@ def _check_max_features(self):
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elif self.max_features is None:
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max_features = self.n_features_in_
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elif isinstance(self.max_features, (Integral, np.integer)):
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elif isinstance(self.max_features, Integral):
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max_features = self.max_features
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else: # float
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if self.max_features > 0.0:

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