8000 update docstrings for all classes · scikit-learn/scikit-learn@cf72fd4 · GitHub
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update docstrings for all classes
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‎sklearn/ensemble/forest.py

Lines changed: 5 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -809,8 +809,7 @@ class RandomForestClassifier(ForestClassifier):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided, but
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min_samples_leaf is more efficient.
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow trees with ``max_leaf_nodes`` in best-first fashion.
@@ -1022,8 +1021,7 @@ class RandomForestRegressor(ForestRegressor):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided, but
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min_samples_leaf is more efficient.
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow trees with ``max_leaf_nodes`` in best-first fashion.
@@ -1195,8 +1193,7 @@ class ExtraTreesClassifier(ForestClassifier):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided, but
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min_samples_leaf is more efficient.
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow trees with ``max_leaf_nodes`` in best-first fashion.
@@ -1407,8 +1404,7 @@ class ExtraTreesRegressor(ForestRegressor):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided, but
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min_samples_leaf is more efficient.
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow trees with ``max_leaf_nodes`` in best-first fashion.
@@ -1566,8 +1562,7 @@ class RandomTreesEmbedding(BaseForest):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided, but
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min_samples_leaf is more efficient.
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow trees with ``max_leaf_nodes`` in best-first fashion.

‎sklearn/ensemble/gradient_boosting.py

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1331,7 +1331,8 @@ class GradientBoostingClassifier(BaseGradientBoosting, ClassifierMixin):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node.
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided.
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subsample : float, optional (default=1.0)
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The fraction of samples to be used for fitting the individual base
@@ -1699,7 +1700,8 @@ class GradientBoostingRegressor(BaseGradientBoosting, RegressorMixin):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node.
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided.
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subsample : float, optional (default=1.0)
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The fraction of samples to be used for fitting the individual base

‎sklearn/tree/tree.py

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -594,7 +594,8 @@ class DecisionTreeClassifier(BaseDecisionTree, ClassifierMixin):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node.
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow a tree with ``max_leaf_nodes`` in best-first fashion.
@@ -864,7 +865,8 @@ class DecisionTreeRegressor(BaseDecisionTree, RegressorMixin):
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min_weight_fraction_leaf : float, optional (default=0.)
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The minimum weighted fraction of the sum total of weights (of all
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the input samples) required to be at a leaf node.
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the input samples) required to be at a leaf node. Samples have
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equal weight when sample_weight is not provided.
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max_leaf_nodes : int or None, optional (default=None)
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Grow a tree with ``max_leaf_nodes`` in best-first fashion.

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