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Make the default value of n_features match the khiops core value #545

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Merged
tramora merged 1 commit into from
Feb 13, 2026
+22 −10
Merged

Make the default value of n_features match the khiops core value #545

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7 changes: 5 additions & 2 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -9,11 +9,14 @@
## Unreleased

### Added
- (`sklearn`) `n_feature_parts` parameter to the supervised estimators
- (`sklearn`) `n_feature_parts` parameter to the supervised estimators

### Fixed
- (`sklearn`) Default value of `n_features` for the supervised estimators

## 11.0.0.2 - 2026-01-26

## Fixed
### Fixed
- (`core`) Samples dir path construction when HOME is a remote path

## 11.0.0.1 - 2026-01-14
Expand Down
16 changes: 8 additions & 8 deletions khiops/sklearn/estimators.py
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Expand Up @@ -1188,7 +1188,7 @@ class KhiopsSupervisedEstimator(KhiopsEstimator):

def __init__(
self,
n_features=100,
n_features=1000,
n_trees=10,
n_text_features=10000,
type_text_features="words",
Expand Down Expand Up @@ -1513,7 +1513,7 @@ class KhiopsPredictor(KhiopsSupervisedEstimator):

def __init__(
self,
n_features=100,
n_features=1000,
n_trees=10,
n_text_features=10000,
type_text_features="words",
Expand Down Expand Up @@ -1656,7 +1656,7 @@ class KhiopsClassifier(ClassifierMixin, KhiopsPredictor):

Parameters
----------
n_features : int, default 100
n_features : int, default 1000
Maximum number of features to construct automatically. See
:doc:`/multi_table_primer` for more details on the multi-table-specific
features.
Expand Down Expand Up @@ -1748,7 +1748,7 @@ class KhiopsClassifier(ClassifierMixin, KhiopsPredictor):

def __init__(
self,
n_features=100,
n_features=1000,
n_pairs=0,
n_trees=10,
n_text_features=10000,
Expand Down Expand Up @@ -2076,7 +2076,7 @@ class KhiopsRegressor(RegressorMixin, KhiopsPredictor):

Parameters
----------
n_features : int, default 100
n_features : int, default 1000
Maximum number of features to construct automatically. See
:doc:`/multi_table_primer` for more details on the multi-table-specific
features.
Expand Down Expand Up @@ -2141,7 +2141,7 @@ class KhiopsRegressor(RegressorMixin, KhiopsPredictor):

def __init__(
self,
n_features=100,
n_features=1000,
n_trees=0,
n_text_features=10000,
type_text_features="words",
Expand Down Expand Up @@ -2283,7 +2283,7 @@ class KhiopsEncoder(TransformerMixin, KhiopsSupervisedEstimator):
----------
categorical_target : bool, default ``True``
``True`` if the target column is categorical.
n_features : int, default 100
n_features : int, default 1000
Maximum number of features to construct automatically. See
:doc:`/multi_table_primer` for more details on the multi-table-specific
features.
Expand Down Expand Up @@ -2390,7 +2390,7 @@ class KhiopsEncoder(TransformerMixin, KhiopsSupervisedEstimator):
def __init__(
self,
categorical_target=True,
n_features=100,
n_features=1000,
n_pairs=0,
n_trees=0,
n_text_features=10000,
Expand Down
9 changes: 9 additions & 0 deletions tests/test_sklearn.py
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Expand Up @@ -753,6 +753,7 @@ def setUpClass(cls):
"field_separator": "\t",
"detect_format": False,
"header_line": True,
"max_constructed_variables": 333,
"max_pairs": 1,
"max_trees": 5,
"max_text_features": 300000,
Expand Down Expand Up @@ -785,6 +786,7 @@ def setUpClass(cls):
"field_separator": "\t",
"detect_format": False,
"header_line": True,
"max_constructed_variables": 555,
"max_trees": 0,
"max_text_features": 300000,
"text_features": "ngrams",
Expand Down Expand Up @@ -813,6 +815,7 @@ def setUpClass(cls):
"field_separator": "\t",
"detect_format": False,
"header_line": True,
"max_constructed_variables": 777,
"max_pairs": 1,
"max_trees": 5,
"max_text_features": 300000,
Expand Down Expand Up @@ -1432,6 +1435,7 @@ def test_parameter_transfer_classifier_fit_from_monotable_dataframe(self):
schema_type="monotable",
source_type="dataframe",
extra_estimator_kwargs={
"n_features": 333,
"n_pairs": 1,
"n_trees": 5,
"n_text_features": 300000,
Expand All @@ -1456,6 +1460,7 @@ def test_parameter_transfer_classifier_fit_from_monotable_dataframe_with_df_y(
schema_type="monotable",
source_type="dataframe_xy",
extra_estimator_kwargs={
"n_features": 333,
"n_pairs": 1,
"n_trees": 5,
"n_text_features": 300000,
Expand Down Expand Up @@ -1519,6 +1524,7 @@ def test_parameter_transfer_encoder_fit_from_monotable_dataframe(self):
schema_type="monotable",
source_type="dataframe",
extra_estimator_kwargs={
"n_features": 777,
"n_pairs": 1,
"n_trees": 5,
"n_text_features": 300000,
Expand Down Expand Up @@ -1546,6 +1552,7 @@ def test_parameter_transfer_encoder_fit_from_monotable_dataframe_with_df_y(
schema_type="monotable",
source_type="dataframe_xy",
extra_estimator_kwargs={
"n_features": 777,
"n_pairs": 1,
"n_trees": 5,
"n_text_features": 300000,
Expand Down Expand Up @@ -1615,6 +1622,7 @@ def test_parameter_transfer_regressor_fit_from_monotable_dataframe(self):
schema_type="monotable",
source_type="dataframe",
extra_estimator_kwargs={
"n_features": 555,
"n_selected_features": 1,
"n_evaluated_features": 3,
"n_text_features": 300000,
Expand All @@ -1634,6 +1642,7 @@ def test_parameter_transfer_regressor_fit_from_monotable_dataframe_with_df_y(
schema_type="monotable",
source_type="dataframe_xy",
extra_estimator_kwargs={
"n_features": 555,
"n_selected_features": 1,
"n_evaluated_features": 3,
"n_text_features": 300000,
Expand Down
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