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FIX correct the invoke of oblique trees by feature combinations #347

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FIX correct the invoke of oblique trees by feature combinations #347

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3e4384c
make feature_combination into use
mamamum Feb 19, 2025
3b83ee4
make feature_combination into use
mamamum Feb 25, 2025
a84ff1c
Merge branch 'main' into main
YuxinB Mar 8, 2025
5bc1284
make feature_combination into use
mamamum Mar 11, 2025
4e3ddc5
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 11, 2025
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13 changes: 10 additions & 3 deletions treeple/tree/_multiview.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,14 @@ class MultiViewDecisionTreeClassifier(SimMatrixMixin, DecisionTreeClassifier):
through the fit method) if sample_weight is specified.

feature_combinations : float, default=None
Not used.
The number of features to combine on average at each split
of the decision trees. If ``None``, then will default to the minimum of
1. This controls the number of non-zeros is the
projection matrix. Setting the value to 1.0 is equivalent to a
traditional decision-tree. ``feature_combinations * max_features``
gives the number of expected non-zeros in the projection matrix of shape
``(max_features, n_features)``. Thus this value must always be less than
``n_features`` in order to be valid.

ccp_alpha : non-negative float, default=0.0
Not used.
Expand Down Expand Up @@ -303,7 +310,7 @@ def __init__(
monotonic_cst=monotonic_cst,
)

self.feature_combinations = feature_combinations
self.feature_combinations = 1 if feature_combinations is None else feature_combinations
self.feature_set_ends = feature_set_ends
self.apply_max_features_per_feature_set = apply_max_features_per_feature_set
self._max_features_arr = None
Expand Down Expand Up @@ -364,7 +371,7 @@ def _build_tree(
self.monotonic_cst_ = monotonic_cst
_, n_features = X.shape

self.feature_combinations_ = 1
self.feature_combinations_ = self.feature_combinations

# Build tree
criterion = self.criterion
Expand Down
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