diff --git a/src/safeds/ml/classification/_ada_boost.py b/src/safeds/ml/classification/_ada_boost.py index 2eabb311d..a1fff3dcd 100644 --- a/src/safeds/ml/classification/_ada_boost.py +++ b/src/safeds/ml/classification/_ada_boost.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -37,7 +35,7 @@ def fit(self, tagged_table: TaggedTable) -> None: self._classification, tagged_table ) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -45,8 +43,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -61,5 +57,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._classification, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/classification/_classifier.py b/src/safeds/ml/classification/_classifier.py index b3b045ac7..ea3d19c60 100644 --- a/src/safeds/ml/classification/_classifier.py +++ b/src/safeds/ml/classification/_classifier.py @@ -1,5 +1,4 @@ from abc import ABC, abstractmethod -from typing import Optional from safeds.data.tabular.containers import Table, TaggedTable @@ -22,7 +21,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ @abstractmethod - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -30,8 +29,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- diff --git a/src/safeds/ml/classification/_decision_tree.py b/src/safeds/ml/classification/_decision_tree.py index bae5c1397..cdbc2f571 100644 --- a/src/safeds/ml/classification/_decision_tree.py +++ b/src/safeds/ml/classification/_decision_tree.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -37,7 +35,7 @@ def fit(self, tagged_table: TaggedTable) -> None: self._classification, tagged_table ) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -45,8 +43,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -61,5 +57,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._classification, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/classification/_gradient_boosting_classification.py b/src/safeds/ml/classification/_gradient_boosting_classification.py index 999f8771f..636efa8dd 100644 --- a/src/safeds/ml/classification/_gradient_boosting_classification.py +++ b/src/safeds/ml/classification/_gradient_boosting_classification.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -38,7 +36,7 @@ def fit(self, tagged_table: TaggedTable) -> None: ) # noinspection PyProtectedMember - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -46,8 +44,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -62,5 +58,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._classification, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/classification/_k_nearest_neighbors.py b/src/safeds/ml/classification/_k_nearest_neighbors.py index 547ebfbbd..065f08d80 100644 --- a/src/safeds/ml/classification/_k_nearest_neighbors.py +++ b/src/safeds/ml/classification/_k_nearest_neighbors.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -41,7 +39,7 @@ def fit(self, tagged_table: TaggedTable) -> None: self._classification, tagged_table ) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first @@ -49,8 +47,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -65,5 +61,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._classification, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/classification/_logistic_regression.py b/src/safeds/ml/classification/_logistic_regression.py index 45c759dbc..53d3f0221 100644 --- a/src/safeds/ml/classification/_logistic_regression.py +++ b/src/safeds/ml/classification/_logistic_regression.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -37,7 +35,7 @@ def fit(self, tagged_table: TaggedTable) -> None: self._classification, tagged_table ) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -45,8 +43,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -61,5 +57,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._classification, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/classification/_random_forest.py b/src/safeds/ml/classification/_random_forest.py index ae4318c7b..5ff5599f0 100644 --- a/src/safeds/ml/classification/_random_forest.py +++ b/src/safeds/ml/classification/_random_forest.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -36,7 +34,7 @@ def fit(self, tagged_table: TaggedTable) -> None: self._classification, tagged_table ) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -44,8 +42,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -60,5 +56,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._classification, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_ada_boost.py b/src/safeds/ml/regression/_ada_boost.py index 2b25dfa13..8968f8fc7 100644 --- a/src/safeds/ml/regression/_ada_boost.py +++ b/src/safeds/ml/regression/_ada_boost.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -35,7 +33,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -43,8 +41,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -59,5 +55,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_decision_tree.py b/src/safeds/ml/regression/_decision_tree.py index c4b242e4d..c3dc49b89 100644 --- a/src/safeds/ml/regression/_decision_tree.py +++ b/src/safeds/ml/regression/_decision_tree.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -35,7 +33,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -43,8 +41,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name: Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -59,5 +55,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_elastic_net_regression.py b/src/safeds/ml/regression/_elastic_net_regression.py index b8cd5da06..be7c54213 100644 --- a/src/safeds/ml/regression/_elastic_net_regression.py +++ b/src/safeds/ml/regression/_elastic_net_regression.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -35,7 +33,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -43,8 +41,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name: Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -59,5 +55,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_gradient_boosting_regression.py b/src/safeds/ml/regression/_gradient_boosting_regression.py index bd3d9672d..fe68ad31a 100644 --- a/src/safeds/ml/regression/_gradient_boosting_regression.py +++ b/src/safeds/ml/regression/_gradient_boosting_regression.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -37,7 +35,7 @@ def fit(self, tagged_table: TaggedTable) -> None: self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) # noinspection PyProtectedMember - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -45,8 +43,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -61,5 +57,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_k_nearest_neighbors.py b/src/safeds/ml/regression/_k_nearest_neighbors.py index ecda4d539..b8d7b9b4b 100644 --- a/src/safeds/ml/regression/_k_nearest_neighbors.py +++ b/src/safeds/ml/regression/_k_nearest_neighbors.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -39,7 +37,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -47,8 +45,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name: Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -63,5 +59,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_lasso_regression.py b/src/safeds/ml/regression/_lasso_regression.py index 88c79eb9c..3ab76ffd4 100644 --- a/src/safeds/ml/regression/_lasso_regression.py +++ b/src/safeds/ml/regression/_lasso_regression.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -35,7 +33,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -43,8 +41,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name: Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -59,5 +55,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_linear_regression.py b/src/safeds/ml/regression/_linear_regression.py index 6d748ed2c..0599433dd 100644 --- a/src/safeds/ml/regression/_linear_regression.py +++ b/src/safeds/ml/regression/_linear_regression.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -35,7 +33,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -43,8 +41,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name: Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -59,5 +55,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_random_forest.py b/src/safeds/ml/regression/_random_forest.py index 3bef1a3cf..d1eec68e6 100644 --- a/src/safeds/ml/regression/_random_forest.py +++ b/src/safeds/ml/regression/_random_forest.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -34,7 +32,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -42,8 +40,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- @@ -58,5 +54,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, ) diff --git a/src/safeds/ml/regression/_regressor.py b/src/safeds/ml/regression/_regressor.py index 893fa689b..1cb166f1b 100644 --- a/src/safeds/ml/regression/_regressor.py +++ b/src/safeds/ml/regression/_regressor.py @@ -1,5 +1,4 @@ from abc import ABC, abstractmethod -from typing import Optional from safeds.data.tabular.containers import Table, TaggedTable @@ -22,7 +21,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ @abstractmethod - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -30,8 +29,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name: Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default. Returns ------- diff --git a/src/safeds/ml/regression/_ridge_regression.py b/src/safeds/ml/regression/_ridge_regression.py index bff53857d..3aa99bf4b 100644 --- a/src/safeds/ml/regression/_ridge_regression.py +++ b/src/safeds/ml/regression/_ridge_regression.py @@ -1,5 +1,3 @@ -from typing import Optional - # noinspection PyProtectedMember import safeds.ml._util_sklearn from safeds.data.tabular.containers import Table, TaggedTable @@ -35,7 +33,7 @@ def fit(self, tagged_table: TaggedTable) -> None: """ self.target_name = safeds.ml._util_sklearn.fit(self._regression, tagged_table) - def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: + def predict(self, dataset: Table) -> Table: """ Predict a target vector using a dataset containing feature vectors. The model has to be trained first. @@ -43,8 +41,6 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: ---------- dataset : Table The dataset containing the feature vectors. - target_name : Optional[str] - The name of the target vector. The name of the target column inferred from fit is used by default Returns ------- @@ -59,5 +55,5 @@ def predict(self, dataset: Table, target_name: Optional[str] = None) -> Table: return safeds.ml._util_sklearn.predict( self._regression, dataset, - target_name if target_name is not None else self.target_name, + self.target_name, )