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Thierry RAMORASOAVINA
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Add the n_feature_parts parameter to the supervised estimators
- KhiopsClassifier, KhiopsRegressor and KhiopsEncoder
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‎CHANGELOG.md‎

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Original file line numberDiff line numberDiff line change
@@ -6,6 +6,11 @@
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- Example: 10.2.1.4 is the 5th version that supports khiops 10.2.1.
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- Internals: Changes in *Internals* sections are unlikely to be of interest for data scientists.
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## Unreleased
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### Added
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- (`sklearn`) `n_feature_parts` parameter to the supervised estimators
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## 11.0.0.2 - 2026-01-26
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## Fixed

‎khiops/sklearn/estimators.py‎

Lines changed: 27 additions & 1 deletion
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@@ -1195,6 +1195,7 @@ def __init__(
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specific_pairs=None,
11961196
all_possible_pairs=True,
11971197
construction_rules=None,
1198+
n_feature_parts=0,
11981199
verbose=False,
11991200
output_dir=None,
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auto_sort=True,
@@ -1211,6 +1212,7 @@ def __init__(
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self.specific_pairs = specific_pairs
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self.all_possible_pairs = all_possible_pairs
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self.construction_rules = construction_rules
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self.n_feature_parts = n_feature_parts
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self._original_target_dtype = None
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self._predicted_target_meta_data_tag = None
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self._khiops_baseline_model_prefix = None
@@ -1300,6 +1302,12 @@ def _fit_check_params(self, ds, **kwargs):
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for rule in self.construction_rules:
13011303
if not isinstance(rule, str):
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raise TypeError(type_error_message(rule, rule, str))
1305+
if not isinstance(self.n_feature_parts, int):
1306+
raise TypeError(
1307+
type_error_message("n_feature_parts", self.n_feature_parts, int)
1308+
)
1309+
if self.n_feature_parts < 0:
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raise ValueError("'n_feature_parts' must be positive")
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13041312
def _fit_train_model(self, ds, computation_dir, **kwargs):
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# Train the model with Khiops
@@ -1384,6 +1392,7 @@ def _fit_prepare_training_function_inputs(self, ds, computation_dir):
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kwargs["max_trees"] = kwargs.pop("n_trees")
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kwargs["max_text_features"] = kwargs.pop("n_text_features")
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kwargs["text_features"] = kwargs.pop("type_text_features")
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kwargs["max_parts"] = kwargs.pop("n_feature_parts")
13871396

13881397
# Add the additional_data_tables parameter
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kwargs["additional_data_tables"] = additional_data_tables
@@ -1513,6 +1522,7 @@ def __init__(
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specific_pairs=None,
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all_possible_pairs=True,
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construction_rules=None,
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n_feature_parts=0,
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verbose=False,
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output_dir=None,
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auto_sort=True,
@@ -1525,6 +1535,7 @@ def __init__(
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specific_pairs=specific_pairs,
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all_possible_pairs=all_possible_pairs,
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construction_rules=construction_rules,
1538+
n_feature_parts=n_feature_parts,
15281539
verbose=verbose,
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output_dir=output_dir,
15301541
auto_sort=auto_sort,
@@ -1685,7 +1696,10 @@ class KhiopsClassifier(ClassifierMixin, KhiopsPredictor):
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construction_rules : list of str, optional
16861697
Allowed rules for the automatic feature construction. If not set, Khiops
16871698
uses the multi-table construction rules listed in
1688-
`kh.DEFAULT_CONSTRUCTION_RULES <khiops.core.api.DEFAULT_CONSTRUCTION_RULES>`
1699+
`kh.DEFAULT_CONSTRUCTION_RULES <khiops.core.api.DEFAULT_CONSTRUCTION_RULES>`.
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n_feature_parts : int, default 0
1701+
Maximum number of variable parts produced by preprocessing methods. If equal
1702+
to 0 it is automatically calculated.
16891703
group_target_value : bool, default ``False``
16901704
Allows grouping of the target values in classification. It can substantially
16911705
increase the training time.
@@ -1744,6 +1758,7 @@ def __init__(
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specific_pairs=None,
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all_possible_pairs=True,
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construction_rules=None,
1761+
n_feature_parts=0,
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group_target_value=False,
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verbose=False,
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output_dir=None,
@@ -1757,6 +1772,7 @@ def __init__(
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n_selected_features=n_selected_features,
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n_evaluated_features=n_evaluated_features,
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construction_rules=construction_rules,
1775+
n_feature_parts=n_feature_parts,
17601776
verbose=verbose,
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output_dir=output_dir,
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auto_sort=auto_sort,
@@ -2086,6 +2102,9 @@ class KhiopsRegressor(RegressorMixin, KhiopsPredictor):
20862102
Allowed rules for the automatic feature construction. If not set, Khiops
20872103
uses the multi-table construction rules listed in
20882104
`kh.DEFAULT_CONSTRUCTION_RULES <khiops.core.api.DEFAULT_CONSTRUCTION_RULES>`.
2105+
n_feature_parts : int, default 0
2106+
Maximum number of variable parts produced by preprocessing methods. If equal
2107+
to 0 it is automatically calculated.
20892108
verbose : bool, default ``False``
20902109
If ``True`` it prints debug information and it does not erase temporary files
20912110
when fitting, predicting or transforming.
@@ -2129,6 +2148,7 @@ def __init__(
21292148
n_selected_features=0,
21302149
n_evaluated_features=0,
21312150
construction_rules=None,
2151+
n_feature_parts=0,
21322152
verbose=False,
21332153
output_dir=None,
21342154
auto_sort=True,
@@ -2141,6 +2161,7 @@ def __init__(
21412161
n_selected_features=n_selected_features,
21422162
n_evaluated_features=n_evaluated_features,
21432163
construction_rules=construction_rules,
2164+
n_feature_parts=n_feature_parts,
21442165
verbose=verbose,
21452166
output_dir=output_dir,
21462167
auto_sort=auto_sort,
@@ -2296,6 +2317,9 @@ class KhiopsEncoder(TransformerMixin, KhiopsSupervisedEstimator):
22962317
Allowed rules for the automatic feature construction. If not set, Khiops
22972318
uses the multi-table construction rules listed in
22982319
`kh.DEFAULT_CONSTRUCTION_RULES <khiops.core.api.DEFAULT_CONSTRUCTION_RULES>`.
2320+
n_feature_parts : int, default 0
2321+
Maximum number of variable parts produced by preprocessing methods. If equal
2322+
to 0 it is automatically calculated.
22992323
informative_features_only : bool, default ``True``
23002324
If ``True`` keeps only informative features.
23012325
group_target_value : bool, default ``False``
@@ -2374,6 +2398,7 @@ def __init__(
23742398
specific_pairs=None,
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all_possible_pairs=True,
23762400
construction_rules=None,
2401+
n_feature_parts=0,
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informative_features_only=True,
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group_target_value=False,
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keep_initial_variables=False,
@@ -2390,6 +2415,7 @@ def __init__(
23902415
n_text_features=n_text_features,
23912416
type_text_features=type_text_features,
23922417
construction_rules=construction_rules,
2418+
n_feature_parts=n_feature_parts,
23932419
verbose=verbose,
23942420
output_dir=output_dir,
23952421
auto_sort=auto_sort,

‎tests/test_sklearn.py‎

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Original file line numberDiff line numberDiff line change
@@ -762,6 +762,7 @@ def setUpClass(cls):
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"specific_pairs": [("age", "race")],
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"all_possible_pairs": False,
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"construction_rules": ["TableMode", "TableSelection"],
765+
"max_parts": 3,
765766
"group_target_value": False,
766767
"additional_data_tables": {},
767768
}
@@ -790,6 +791,7 @@ def setUpClass(cls):
790791
"max_selected_variables": 1,
791792
"max_evaluated_variables": 3,
792793
"construction_rules": ["TableMode", "TableSelection"],
794+
"max_parts": 5,
793795
"additional_data_tables": {},
794796
}
795797
},
@@ -818,6 +820,7 @@ def setUpClass(cls):
818820
"specific_pairs": [("age", "race")],
819821
"all_possible_pairs": False,
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"construction_rules": ["TableMode", "TableSelection"],
823+
"max_parts": 7,
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"informative_variables_only": True,
822825
"group_target_value": False,
823826
"keep_initial_categorical_variables": False,
@@ -860,6 +863,7 @@ def setUpClass(cls):
860863
"specific_pairs": [],
861864
"all_possible_pairs": False,
862865
"construction_rules": ["TableMode", "TableSelection"],
866+
"max_parts": 4,
863867
"group_target_value": False,
864868
"additional_data_tables": {"SpliceJunctionDNA"},
865869
}
@@ -889,6 +893,7 @@ def setUpClass(cls):
889893
"max_selected_variables": 1,
890894
"max_evaluated_variables": 3,
891895
"construction_rules": ["TableMode", "TableSelection"],
896+
"max_parts": 6,
892897
"additional_data_tables": {"SpliceJunctionDNA"},
893898
}
894899
},
@@ -918,6 +923,7 @@ def setUpClass(cls):
918923
"specific_pairs": [],
919924
"all_possible_pairs": False,
920925
"construction_rules": ["TableMode", "TableSelection"],
926+
"max_parts": 8,
921927
"informative_variables_only": True,
922928
"group_target_value": False,
923929
"keep_initial_categorical_variables": False,
@@ -1435,6 +1441,7 @@ def test_parameter_transfer_classifier_fit_from_monotable_dataframe(self):
14351441
"specific_pairs": [("age", "race")],
14361442
"all_possible_pairs": False,
14371443
"construction_rules": ["TableMode", "TableSelection"],
1444+
"n_feature_parts": 3,
14381445
"group_target_value": False,
14391446
},
14401447
)
@@ -1458,6 +1465,7 @@ def test_parameter_transfer_classifier_fit_from_monotable_dataframe_with_df_y(
14581465
"specific_pairs": [("age", "race")],
14591466
"all_possible_pairs": False,
14601467
"construction_rules": ["TableMode", "TableSelection"],
1468+
"n_feature_parts": 3,
14611469
"group_target_value": False,
14621470
},
14631471
)
@@ -1480,6 +1488,7 @@ def test_parameter_transfer_classifier_fit_from_multitable_dataframe(self):
14801488
"specific_pairs": [],
14811489
"all_possible_pairs": False,
14821490
"construction_rules": ["TableMode", "TableSelection"],
1491+
"n_feature_parts": 4,
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"group_target_value": False,
14841493
},
14851494
)
@@ -1517,6 +1526,7 @@ def test_parameter_transfer_encoder_fit_from_monotable_dataframe(self):
15171526
"specific_pairs": [("age", "race")],
15181527
"all_possible_pairs": False,
15191528
"construction_rules": ["TableMode", "TableSelection"],
1529+
"n_feature_parts": 7,
15201530
"informative_features_only": True,
15211531
"group_target_value": False,
15221532
"keep_initial_variables": False,
@@ -1543,6 +1553,7 @@ def test_parameter_transfer_encoder_fit_from_monotable_dataframe_with_df_y(
15431553
"specific_pairs": [("age", "race")],
15441554
"all_possible_pairs": False,
15451555
"construction_rules": ["TableMode", "TableSelection"],
1556+
"n_feature_parts": 7,
15461557
"informative_features_only": True,
15471558
"group_target_value": False,
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"keep_initial_variables": False,
@@ -1568,6 +1579,7 @@ def test_parameter_transfer_encoder_fit_from_multitable_dataframe(self):
15681579
"specific_pairs": [],
15691580
"all_possible_pairs": False,
15701581
"construction_rules": ["TableMode", "TableSelection"],
1582+
"n_feature_parts": 8,
15711583
"informative_features_only": True,
15721584
"group_target_value": False,
15731585
"keep_initial_variables": False,
@@ -1608,6 +1620,7 @@ def test_parameter_transfer_regressor_fit_from_monotable_dataframe(self):
16081620
"n_text_features": 300000,
16091621
"type_text_features": "ngrams",
16101622
"construction_rules": ["TableMode", "TableSelection"],
1623+
"n_feature_parts": 5,
16111624
},
16121625
)
16131626

@@ -1626,6 +1639,7 @@ def test_parameter_transfer_regressor_fit_from_monotable_dataframe_with_df_y(
16261639
"n_text_features": 300000,
16271640
"type_text_features": "ngrams",
16281641
"construction_rules": ["TableMode", "TableSelection"],
1642+
"n_feature_parts": 5,
16291643
},
16301644
)
16311645

@@ -1644,6 +1658,7 @@ def test_parameter_transfer_regressor_fit_from_multitable_dataframe(self):
16441658
"n_selected_features": 1,
16451659
"n_evaluated_features": 3,
16461660
"construction_rules": ["TableMode", "TableSelection"],
1661+
"n_feature_parts": 6,
16471662
},
16481663
)
16491664

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