docs: update API docs (#1250)

### Summary of Changes

* Use operators when working with cells in examples
* Regenerate API docs

docs/api/safeds/data/tabular/containers/Column.md

@@ -127,13 +127,13 @@ pipeline example {
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.all((cell) -> cell.gt(0)); // true
+         *     val result = column.all((cell) -> cell > 0); // true
          * }
          *
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.all((cell) -> cell.lt(3)); // false
+         *     val result = column.all((cell) -> cell < 3); // false
          * }
          */
         @Pure
@@ -170,13 +170,13 @@ pipeline example {
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.any((cell) -> cell.gt(2)); // true
+         *     val result = column.any((cell) -> cell > 2); // true
          * }
          *
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.any((cell) -> cell.lt(0)); // false
+         *     val result = column.any((cell) -> cell < 0); // false
          * }
          */
         @Pure
@@ -208,13 +208,13 @@ pipeline example {
          * @example
          * pipeline example {
          *    val column = Column("test", [1, 2, 3]);
-         *    val result = column.countIf((cell) -> cell.gt(1)); // 2
+         *    val result = column.countIf((cell) -> cell > 1); // 2
          * }
          *
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.countIf((cell) -> cell.lt(0)); // 0
+         *     val result = column.countIf((cell) -> cell < 0); // 0
          * }
          */
         @Pure
@@ -251,13 +251,13 @@ pipeline example {
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.none((cell) -> cell.lt(0)); // true
+         *     val result = column.none((cell) -> cell < 0); // true
          * }
          *
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.none((cell) -> cell.gt(2)); // false
+         *     val result = column.none((cell) -> cell > 2); // false
          * }
          */
         @Pure
@@ -299,7 +299,7 @@ pipeline example {
          * @example
          * pipeline example {
          *     val column = Column("test", [1, 2, 3]);
-         *     val result = column.transform((cell) -> cell.mul(2));
+         *     val result = column.transform((cell) -> cell * 2);
          *     // Column("test", [2, 4, 6])
          * }
          */
@@ -683,13 +683,13 @@ You can instead enable Kleene logic by setting `ignoreUnknown = false`. In this
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.all((cell) -> cell.gt(0)); // true
+    val result = column.all((cell) -> cell > 0); // true
 }
 ```
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.all((cell) -> cell.lt(3)); // false
+    val result = column.all((cell) -> cell < 3); // false
 }
 ```
 
@@ -742,13 +742,13 @@ You can instead enable Kleene logic by setting `ignoreUnknown = false`. In this
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.any((cell) -> cell.gt(2)); // true
+    val result = column.any((cell) -> cell > 2); // true
 }
 ```
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.any((cell) -> cell.lt(0)); // false
+    val result = column.any((cell) -> cell < 0); // false
 }
 ```
 
@@ -846,13 +846,13 @@ if the predicate returns null at least once. Otherwise, it still returns how oft
 ```sds hl_lines="3"
 pipeline example {
    val column = Column("test", [1, 2, 3]);
-   val result = column.countIf((cell) -> cell.gt(1)); // 2
+   val result = column.countIf((cell) -> cell > 1); // 2
 }
 ```
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.countIf((cell) -> cell.lt(0)); // 0
+    val result = column.countIf((cell) -> cell < 0); // 0
 }
 ```
 
@@ -1246,13 +1246,13 @@ You can instead enable Kleene logic by setting `ignoreUnknown = false`. In this
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.none((cell) -> cell.lt(0)); // true
+    val result = column.none((cell) -> cell < 0); // true
 }
 ```
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.none((cell) -> cell.gt(2)); // false
+    val result = column.none((cell) -> cell > 2); // false
 }
 ```
 
@@ -1475,7 +1475,7 @@ Return a new column with values transformed by the transformer.
 ```sds hl_lines="3"
 pipeline example {
     val column = Column("test", [1, 2, 3]);
-    val result = column.transform((cell) -> cell.mul(2));
+    val result = column.transform((cell) -> cell * 2);
     // Column("test", [2, 4, 6])
 }
 ```

docs/api/safeds/data/tabular/containers/Row.md

@@ -38,7 +38,7 @@ This class cannot be instantiated directly. It is only used for arguments of cal
          * @example
          * pipeline example {
          *     val table = Table({"col1": [1, 2], "col2": [3, 4]});
-         *     val result = table.removeRows((row) -> row.getValue("col1").eq(1));
+         *     val result = table.removeRows((row) -> row.getValue("col1") == 1);
          *     // Table({"col1": [2], "col2": [4]})
          * }
          */
@@ -141,7 +141,7 @@ Get the value of the specified column. This WILL LATER BE equivalent to using th
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"col1": [1, 2], "col2": [3, 4]});
-    val result = table.removeRows((row) -> row.getValue("col1").eq(1));
+    val result = table.removeRows((row) -> row.getValue("col1") == 1);
     // Table({"col1": [2], "col2": [4]})
 }
 ```

docs/api/safeds/data/tabular/containers/Table.md

@@ -190,7 +190,7 @@ pipeline example {
          * @example
          * pipeline example {
          *     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-         *     val result = table.addComputedColumn("c", (row) -> row.getValue("a").add(row.getValue("b")));
+         *     val result = table.addComputedColumn("c", (row) -> row.getValue("a") + row.getValue("b"));
          * }
          */
         @Pure
@@ -434,7 +434,7 @@ pipeline example {
          * @example
          * pipeline example {
          *     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-         *     val result = table.transformColumn("a", (cell) -> cell.add(1));
+         *     val result = table.transformColumn("a", (cell) -> cell + 1);
          *     // Table({"a": [2, 3, 4], "b": [4, 5, 6]})
          * }
          */
@@ -468,13 +468,13 @@ pipeline example {
          * @example
          * pipeline example {
          *     val table = Table({"col1": [1, 2, 3], "col2": [1, 3, 3]});
-         *     val result = table.countRowIf((row) -> row.getValue("col1").eq(row.getValue("col2"))); // 2
+         *     val result = table.countRowIf((row) -> row.getValue("col1") == row.getValue("col2")); // 2
          * }
          *
          * @example
          * pipeline example {
          *     val table = Table({"col1": [1, 2, 3], "col2": [1, 3, 3]});
-         *     val result = table.countRowIf((row) -> row.getValue("col1").gt(row.getValue("col2"))); // 0
+         *     val result = table.countRowIf((row) -> row.getValue("col1") > row.getValue("col2")); // 0
          * }
          */
         @Pure
@@ -514,7 +514,7 @@ pipeline example {
          * @example
          * pipeline example {
          *     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-         *     val result = table.removeRows((row) -> row.getValue("a").eq(2));
+         *     val result = table.removeRows((row) -> row.getValue("a") == 2);
          *     // Table({"a": [1, 3], "b": [4, 6]})
          * }
          */
@@ -537,7 +537,7 @@ pipeline example {
          * @example
          * pipeline example {
          *     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-         *     val result = table.removeRowsByColumn("a", (cell) -> cell.eq(2));
+         *     val result = table.removeRowsByColumn("a", (cell) -> cell == 2);
          *     // Table({"a": [1, 3], "b": [4, 6]})
          * }
          */
@@ -673,7 +673,7 @@ pipeline example {
          * @example
          * pipeline example {
          *     val table = Table({"a": [2, 1, 3], "b": [1, 1, 2]});
-         *     val result = table.sortRows((row) -> row.getValue("a").^sub(row.getValue("b")));
+         *     val result = table.sortRows((row) -> row.getValue("a") - row.getValue("b"));
          *     // Table({"a": [1, 2, 3], "b": [1, 1, 2]})
          * }
          */
@@ -1147,7 +1147,7 @@ Return a new table with an additional computed column.
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-    val result = table.addComputedColumn("c", (row) -> row.getValue("a").add(row.getValue("b")));
+    val result = table.addComputedColumn("c", (row) -> row.getValue("a") + row.getValue("b"));
 }
 ```
 
@@ -1280,13 +1280,13 @@ if the predicate returns null at least once. Otherwise, it still returns how oft
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"col1": [1, 2, 3], "col2": [1, 3, 3]});
-    val result = table.countRowIf((row) -> row.getValue("col1").eq(row.getValue("col2"))); // 2
+    val result = table.countRowIf((row) -> row.getValue("col1") == row.getValue("col2")); // 2
 }
 ```
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"col1": [1, 2, 3], "col2": [1, 3, 3]});
-    val result = table.countRowIf((row) -> row.getValue("col1").gt(row.getValue("col2"))); // 0
+    val result = table.countRowIf((row) -> row.getValue("col1") > row.getValue("col2")); // 0
 }
 ```
 
@@ -1690,7 +1690,7 @@ Return a new table without rows that satisfy a condition.
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-    val result = table.removeRows((row) -> row.getValue("a").eq(2));
+    val result = table.removeRows((row) -> row.getValue("a") == 2);
     // Table({"a": [1, 3], "b": [4, 6]})
 }
 ```
@@ -1729,7 +1729,7 @@ Return a new table without rows that satisfy a condition on a specific column.
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-    val result = table.removeRowsByColumn("a", (cell) -> cell.eq(2));
+    val result = table.removeRowsByColumn("a", (cell) -> cell == 2);
     // Table({"a": [1, 3], "b": [4, 6]})
 }
 ```
@@ -2044,7 +2044,7 @@ Return a new table with the rows sorted.
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"a": [2, 1, 3], "b": [1, 1, 2]});
-    val result = table.sortRows((row) -> row.getValue("a").^sub(row.getValue("b")));
+    val result = table.sortRows((row) -> row.getValue("a") - row.getValue("b"));
     // Table({"a": [1, 2, 3], "b": [1, 1, 2]})
 }
 ```
@@ -2452,7 +2452,7 @@ Return a new table with a column transformed.
 ```sds hl_lines="3"
 pipeline example {
     val table = Table({"a": [1, 2, 3], "b": [4, 5, 6]});
-    val result = table.transformColumn("a", (cell) -> cell.add(1));
+    val result = table.transformColumn("a", (cell) -> cell + 1);
     // Table({"a": [2, 3, 4], "b": [4, 5, 6]})
 }
 ```

docs/api/safeds/data/tabular/transformation/TableTransformer.md

@@ -13,7 +13,6 @@ Learn a transformation for a set of columns in a `Table` and transform another `
 
 - [`Discretizer`][safeds.data.tabular.transformation.Discretizer]
 - [`FunctionalTableTransformer`][safeds.data.tabular.transformation.FunctionalTableTransformer]
-- `#!sds Imputer`
 - [`InvertibleTableTransformer`][safeds.data.tabular.transformation.InvertibleTableTransformer]
 - [`KNearestNeighborsImputer`][safeds.data.tabular.transformation.KNearestNeighborsImputer]
 - [`SimpleImputer`][safeds.data.tabular.transformation.SimpleImputer]

docs/api/safeds/ml/classical/classification/Classifier.md

@@ -18,10 +18,8 @@ A model for classification tasks.
 - [`GradientBoostingClassifier`][safeds.ml.classical.classification.GradientBoostingClassifier]
 - [`KNearestNeighborsClassifier`][safeds.ml.classical.classification.KNearestNeighborsClassifier]
 - [`LogisticClassifier`][safeds.ml.classical.classification.LogisticClassifier]
-- `#!sds LogisticRegressionClassifier`
 - [`RandomForestClassifier`][safeds.ml.classical.classification.RandomForestClassifier]
 - [`SupportVectorClassifier`][safeds.ml.classical.classification.SupportVectorClassifier]
-- `#!sds SupportVectorMachineClassifier`
 
 ??? quote "Stub code in `Classifier.sdsstub`"
 

docs/api/safeds/ml/classical/regression/Regressor.md

@@ -19,11 +19,9 @@ A model for regression tasks.
 - [`GradientBoostingRegressor`][safeds.ml.classical.regression.GradientBoostingRegressor]
 - [`KNearestNeighborsRegressor`][safeds.ml.classical.regression.KNearestNeighborsRegressor]
 - [`LassoRegressor`][safeds.ml.classical.regression.LassoRegressor]
-- `#!sds LinearRegressionRegressor`
 - [`LinearRegressor`][safeds.ml.classical.regression.LinearRegressor]
 - [`RandomForestRegressor`][safeds.ml.classical.regression.RandomForestRegressor]
 - [`RidgeRegressor`][safeds.ml.classical.regression.RidgeRegressor]
-- `#!sds SupportVectorMachineRegressor`
 - [`SupportVectorRegressor`][safeds.ml.classical.regression.SupportVectorRegressor]
 
 ??? quote "Stub code in `Regressor.sdsstub`"

docs/api/safeds/ml/nn/NeuralNetworkClassifier.md

@@ -8,7 +8,7 @@ A NeuralNetworkClassifier is a neural network that is used for classification ta
 
 | Name | Type | Description | Default |
 |------|------|-------------|---------|
-| `inputConversion` | `#!sds InputConversion<D, F>` | to convert the input data for the neural network | - |
+| `inputConversion` | [`InputConversion<D, F>`][safeds.ml.nn.converters.InputConversion] | to convert the input data for the neural network | - |
 | `layers` | [`List<Layer>`][safeds.lang.List] | a list of layers for the neural network to learn | - |
 
 **Type parameters:**

docs/api/safeds/ml/nn/NeuralNetworkRegressor.md

@@ -8,7 +8,7 @@ A NeuralNetworkRegressor is a neural network that is used for regression tasks.
 
 | Name | Type | Description | Default |
 |------|------|-------------|---------|
-| `inputConversion` | `#!sds InputConversion<D, F>` | to convert the input data for the neural network | - |
+| `inputConversion` | [`InputConversion<D, F>`][safeds.ml.nn.converters.InputConversion] | to convert the input data for the neural network | - |
 | `layers` | [`List<Layer>`][safeds.lang.List] | a list of layers for the neural network to learn | - |
 
 **Type parameters:**