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feat: allow using tables that already contain target for prediction #687

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May 1, 2024
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feat: allow using tables that already contain target for prediction #687

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3 changes: 0 additions & 3 deletions src/safeds/exceptions/__init__.py
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Expand Up @@ -29,7 +29,6 @@
OutOfBoundsError,
)
from safeds.exceptions._ml import (
DatasetContainsTargetError,
DatasetMissesDataError,
DatasetMissesFeaturesError,
FeatureDataMismatchError,
Expand Down Expand Up @@ -63,7 +62,6 @@
"ValueNotPresentWhenFittedError": "._data:ValueNotPresentWhenFittedError",
"WrongFileExtensionError": "._data:WrongFileExtensionError",
# ML exceptions
"DatasetContainsTargetError": "._ml:DatasetContainsTargetError",
"DatasetMissesDataError": "._ml:DatasetMissesDataError",
"DatasetMissesFeaturesError": "._ml:DatasetMissesFeaturesError",
"FeatureDataMismatchError": "._ml:FeatureDataMismatchError",
Expand Down Expand Up @@ -100,7 +98,6 @@
"ValueNotPresentWhenFittedError",
"WrongFileExtensionError",
# ML exceptions
"DatasetContainsTargetError",
"DatasetMissesDataError",
"DatasetMissesFeaturesError",
"FeatureDataMismatchError",
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14 changes: 0 additions & 14 deletions src/safeds/exceptions/_ml.py
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@@ -1,17 +1,3 @@
class DatasetContainsTargetError(ValueError):
"""
Raised when a dataset contains the target column already.

Parameters
----------
target_name:
The name of the target column.
"""

def __init__(self, target_name: str):
super().__init__(f"Dataset already contains the target column '{target_name}'.")


class DatasetMissesFeaturesError(ValueError):
"""
Raised when a dataset misses feature columns.
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5 changes: 0 additions & 5 deletions src/safeds/ml/classical/_util_sklearn.py
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Expand Up @@ -4,7 +4,6 @@
from safeds.data.labeled.containers import TabularDataset
from safeds.data.tabular.containers import Table
from safeds.exceptions import (
DatasetContainsTargetError,
DatasetMissesDataError,
DatasetMissesFeaturesError,
LearningError,
Expand Down Expand Up @@ -102,8 +101,6 @@ def predict(model: Any, dataset: Table, feature_names: list[str] | None, target_
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand All @@ -118,8 +115,6 @@ def predict(model: Any, dataset: Table, feature_names: list[str] | None, target_
# Validation
if model is None or target_name is None or feature_names is None:
raise ModelNotFittedError
if dataset.has_column(target_name):
raise DatasetContainsTargetError(target_name)
missing_feature_names = [feature_name for feature_name in feature_names if not dataset.has_column(feature_name)]
if missing_feature_names:
raise DatasetMissesFeaturesError(missing_feature_names)
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_ada_boost.py
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Expand Up @@ -170,8 +170,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_classifier.py
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Expand Up @@ -70,8 +70,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_decision_tree.py
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Expand Up @@ -84,8 +84,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_gradient_boosting.py
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Expand Up @@ -141,8 +141,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_k_nearest_neighbors.py
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Expand Up @@ -134,8 +134,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_logistic_regression.py
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Expand Up @@ -84,8 +84,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_random_forest.py
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Expand Up @@ -120,8 +120,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/classification/_support_vector_machine.py
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Expand Up @@ -245,8 +245,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_ada_boost.py
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Expand Up @@ -170,8 +170,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand Down
2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_decision_tree.py
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Expand Up @@ -84,8 +84,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_elastic_net_regression.py
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Expand Up @@ -171,8 +171,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_gradient_boosting.py
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Expand Up @@ -141,8 +141,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_k_nearest_neighbors.py
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Expand Up @@ -136,8 +136,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_lasso_regression.py
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Expand Up @@ -125,8 +125,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
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2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_linear_regression.py
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Expand Up @@ -84,8 +84,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand Down
2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_random_forest.py
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Expand Up @@ -115,8 +115,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand Down
2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_regressor.py
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Expand Up @@ -68,8 +68,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand Down
2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_ridge_regression.py
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Expand Up @@ -126,8 +126,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand Down
2 changes: 0 additions & 2 deletions src/safeds/ml/classical/regression/_support_vector_machine.py
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Expand Up @@ -245,8 +245,6 @@ def predict(self, dataset: Table) -> TabularDataset:
------
ModelNotFittedError
If the model has not been fitted yet.
DatasetContainsTargetError
If the dataset contains the target column already.
DatasetMissesFeaturesError
If the dataset misses feature columns.
PredictionError
Expand Down
6 changes: 0 additions & 6 deletions tests/safeds/ml/classical/classification/test_classifier.py
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Expand Up @@ -6,7 +6,6 @@
import pytest
from safeds.data.tabular.containers import Table
from safeds.exceptions import (
DatasetContainsTargetError,
DatasetMissesDataError,
DatasetMissesFeaturesError,
MissingValuesColumnError,
Expand Down Expand Up @@ -190,11 +189,6 @@ def test_should_raise_if_not_fitted(self, classifier: Classifier, valid_data: Ta
with pytest.raises(ModelNotFittedError):
classifier.predict(valid_data.features)

def test_should_raise_if_dataset_contains_target(self, classifier: Classifier, valid_data: TabularDataset) -> None:
fitted_classifier = classifier.fit(valid_data)
with pytest.raises(DatasetContainsTargetError, match="target"):
fitted_classifier.predict(valid_data.to_table())

def test_should_raise_if_dataset_misses_features(self, classifier: Classifier, valid_data: TabularDataset) -> None:
fitted_classifier = classifier.fit(valid_data)
with pytest.raises(DatasetMissesFeaturesError, match="[feat1, feat2]"):
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6 changes: 0 additions & 6 deletions tests/safeds/ml/classical/regression/test_regressor.py
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Expand Up @@ -8,7 +8,6 @@
from safeds.data.tabular.containers import Column, Table
from safeds.exceptions import (
ColumnLengthMismatchError,
DatasetContainsTargetError,
DatasetMissesDataError,
DatasetMissesFeaturesError,
MissingValuesColumnError,
Expand Down Expand Up @@ -191,11 +190,6 @@ def test_should_raise_if_not_fitted(self, regressor: Regressor, valid_data: Tabu
with pytest.raises(ModelNotFittedError):
regressor.predict(valid_data.features)

def test_should_raise_if_dataset_contains_target(self, regressor: Regressor, valid_data: TabularDataset) -> None:
fitted_regressor = regressor.fit(valid_data)
with pytest.raises(DatasetContainsTargetError, match="target"):
fitted_regressor.predict(valid_data.to_table())

def test_should_raise_if_dataset_misses_features(self, regressor: Regressor, valid_data: TabularDataset) -> None:
fitted_regressor = regressor.fit(valid_data)
with pytest.raises(DatasetMissesFeaturesError, match="[feat1, feat2]"):
Expand Down