feat: move existing ML solutions into safeds.ml.classical package (#…

…213)

Closes #210.

### Summary of Changes

We eventually want to support neural networks as well, which are
supposed to reside in the `safeds.ml.neural` package. We do not want to
have packages with different semantics (classification and regression as
tasks, neural networks as a subset of ML methods) on the same package
level, however. Because of this, we moved the existing methods into the
`safeds.ml.classical` package.

---------

Co-authored-by: megalinter-bot <129584137+megalinter-bot@users.noreply.github.com>

docs/tutorials/machine_learning.ipynb

@@ -54,7 +54,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "from safeds.ml.regression import LinearRegression\n",
+    "from safeds.ml.classical.regression import LinearRegression\n",
     "\n",
     "model = LinearRegression()\n",
     "fitted_model = model.fit(tagged_table)"

src/safeds/ml/classical/__init__.py

@@ -0,0 +1 @@
+"""Classes for classical machine learning, i.e. machine learning that does not use neural networks."""

src/safeds/ml/classification/_ada_boost.py → src/safeds/ml/classical/classification/_ada_boost.py

@@ -4,7 +4,7 @@
 
 from sklearn.ensemble import AdaBoostClassifier as sk_AdaBoostClassifier
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._classifier import Classifier
 

src/safeds/ml/classification/_decision_tree.py → src/safeds/ml/classical/classification/_decision_tree.py

@@ -4,7 +4,7 @@
 
 from sklearn.tree import DecisionTreeClassifier as sk_DecisionTreeClassifier
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._classifier import Classifier
 

src/safeds/ml/classification/_gradient_boosting_classification.py → src/safeds/ml/classical/classification/_gradient_boosting_classification.py

@@ -4,7 +4,7 @@
 
 from sklearn.ensemble import GradientBoostingClassifier as sk_GradientBoostingClassifier
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._classifier import Classifier
 

src/safeds/ml/classification/_k_nearest_neighbors.py → src/safeds/ml/classical/classification/_k_nearest_neighbors.py

@@ -4,7 +4,7 @@
 
 from sklearn.neighbors import KNeighborsClassifier as sk_KNeighborsClassifier
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._classifier import Classifier
 

src/safeds/ml/classification/_logistic_regression.py → src/safeds/ml/classical/classification/_logistic_regression.py

@@ -4,7 +4,7 @@
 
 from sklearn.linear_model import LogisticRegression as sk_LogisticRegression
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._classifier import Classifier
 

src/safeds/ml/classification/_random_forest.py → src/safeds/ml/classical/classification/_random_forest.py

@@ -4,7 +4,7 @@
 
 from sklearn.ensemble import RandomForestClassifier as sk_RandomForestClassifier
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._classifier import Classifier
 

src/safeds/ml/regression/_ada_boost.py → src/safeds/ml/classical/regression/_ada_boost.py

@@ -4,7 +4,7 @@
 
 from sklearn.ensemble import AdaBoostRegressor as sk_AdaBoostRegressor
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_decision_tree.py → src/safeds/ml/classical/regression/_decision_tree.py

@@ -4,7 +4,7 @@
 
 from sklearn.tree import DecisionTreeRegressor as sk_DecisionTreeRegressor
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_elastic_net_regression.py → src/safeds/ml/classical/regression/_elastic_net_regression.py

@@ -4,7 +4,7 @@
 
 from sklearn.linear_model import ElasticNet as sk_ElasticNet
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_gradient_boosting_regression.py → src/safeds/ml/classical/regression/_gradient_boosting_regression.py

@@ -4,7 +4,7 @@
 
 from sklearn.ensemble import GradientBoostingRegressor as sk_GradientBoostingRegressor
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_k_nearest_neighbors.py → src/safeds/ml/classical/regression/_k_nearest_neighbors.py

@@ -4,7 +4,7 @@
 
 from sklearn.neighbors import KNeighborsRegressor as sk_KNeighborsRegressor
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_lasso_regression.py → src/safeds/ml/classical/regression/_lasso_regression.py

@@ -4,7 +4,7 @@
 
 from sklearn.linear_model import Lasso as sk_Lasso
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_linear_regression.py → src/safeds/ml/classical/regression/_linear_regression.py

@@ -4,7 +4,7 @@
 
 from sklearn.linear_model import LinearRegression as sk_LinearRegression
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_random_forest.py → src/safeds/ml/classical/regression/_random_forest.py

@@ -4,7 +4,7 @@
 
 from sklearn.ensemble import RandomForestRegressor as sk_RandomForestRegressor
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

src/safeds/ml/regression/_ridge_regression.py → src/safeds/ml/classical/regression/_ridge_regression.py

@@ -4,7 +4,7 @@
 
 from sklearn.linear_model import Ridge as sk_Ridge
 
-from safeds.ml._util_sklearn import fit, predict
+from safeds.ml.classical._util_sklearn import fit, predict
 
 from ._regressor import Regressor
 

tests/safeds/ml/classification/test_classifier.py → tests/safeds/ml/classical/classification/test_classifier.py

@@ -4,7 +4,7 @@
 
 import pytest
 from safeds.data.tabular.containers import Table, TaggedTable
-from safeds.ml.classification import (
+from safeds.ml.classical.classification import (
     AdaBoost,
     Classifier,
     DecisionTree,

tests/safeds/ml/regression/test_regressor.py → tests/safeds/ml/classical/regression/test_regressor.py

@@ -6,14 +6,7 @@
 import pytest
 from safeds.data.tabular.containers import Column, Table, TaggedTable
 from safeds.data.tabular.exceptions import ColumnLengthMismatchError
-from safeds.ml.exceptions import (
-    DatasetContainsTargetError,
-    DatasetMissesFeaturesError,
-    LearningError,
-    ModelNotFittedError,
-    PredictionError,
-)
-from safeds.ml.regression import (
+from safeds.ml.classical.regression import (
     AdaBoost,
     DecisionTree,
     ElasticNetRegression,
@@ -27,7 +20,14 @@
 )
 
 # noinspection PyProtectedMember
-from safeds.ml.regression._regressor import _check_metrics_preconditions
+from safeds.ml.classical.regression._regressor import _check_metrics_preconditions
+from safeds.ml.exceptions import (
+    DatasetContainsTargetError,
+    DatasetMissesFeaturesError,
+    LearningError,
+    ModelNotFittedError,
+    PredictionError,
+)
 
 if TYPE_CHECKING:
     from _pytest.fixtures import FixtureRequest

tests/safeds/ml/test_util_sklearn.py → tests/safeds/ml/classical/test_util_sklearn.py

@@ -1,7 +1,7 @@
 import warnings
 
 from safeds.data.tabular.containers import Table
-from safeds.ml.regression import LinearRegression
+from safeds.ml.classical.regression import LinearRegression
 
 
 def test_predict_should_not_warn_about_feature_names() -> None: