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Safe-DS · Aug 19, 2024 · b588b53 · b588b53
1 parent 3505277
commit b588b53
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Showing 2 changed files with 6 additions and 8 deletions.
diff --git a/src/safeds/ml/nn/_model.py b/src/safeds/ml/nn/_model.py
@@ -1201,9 +1201,7 @@ def _get_best_cnn_model_column(
         best_model = None
         best_metric_value = None
         for fitted_model in list_of_fitted_models:
-            prediction = self._inverse_one_hot_encode_by_index_of_column(
-                fitted_model.predict(input_data).get_output(),  # type: ignore[attr-defined, arg-type]
-            )
+            prediction = fitted_model.predict(input_data).get_output()  # type: ignore[attr-defined, arg-type]
             if best_model is None:
                 best_model = fitted_model
                 match optimization_metric:
@@ -1280,9 +1278,9 @@ def _get_best_cnn_model_table(
         if positive_class is not None:
             for column_index in range(labels.column_count):
                 # TODO Find out if a column is the positive class, maybe by the column name?
-                # if labels.column_names[column_index] == positive_class:
-                positive_class = labels.column_names[column_index]
-                break
+                if labels.column_names[column_index] == positive_class:
+                    positive_class = labels.column_names[column_index]
+                    break
 
         best_model = None
         best_metric_value = None

diff --git a/tests/safeds/ml/nn/test_model.py b/tests/safeds/ml/nn/test_model.py
@@ -218,7 +218,7 @@ def test_should_raise_when_time_series_classification_with_continuous_data(self,
             )
             model = NeuralNetworkClassifier(
                 InputConversionTimeSeries(),
-                [ForwardLayer(neuron_count=4), LSTMLayer(neuron_count=1)],
+                [ForwardLayer(neuron_count=4), LSTMLayer(neuron_count=3)],
             )
             with pytest.raises(
                 NotImplementedError,
@@ -339,7 +339,7 @@ def test_should_raise_when_time_series_classification_with_continuous_data(self,
             )
             model = NeuralNetworkClassifier(
                 InputConversionTimeSeries(),
-                [ForwardLayer(neuron_count=Choice(2, 4)), LSTMLayer(neuron_count=1)],
+                [ForwardLayer(neuron_count=Choice(2, 4)), LSTMLayer(neuron_count=3)],
             )
             with pytest.raises(
                 NotImplementedError,