diff --git a/code/bolsonaro/models/omp_forest.py b/code/bolsonaro/models/omp_forest.py
index e4a5667b0d759fe1344fe14bb89dcf601c14f610..6c9a3f91587ac6b34cf17f47c6b46d5bb8ce9c54 100644
--- a/code/bolsonaro/models/omp_forest.py
+++ b/code/bolsonaro/models/omp_forest.py
@@ -123,7 +123,9 @@ class SingleOmpForest(OmpForest):
         forest_predictions = self._base_estimator_predictions(X)
 
         if self._models_parameters.normalize_D:
+            forest_predictions = forest_predictions.T
             forest_predictions /= self._forest_norms
+            forest_predictions = forest_predictions.T
 
         return self._make_omp_weighted_prediction(forest_predictions, self._omp, self._models_parameters.normalize_weights)
 
@@ -139,7 +141,9 @@ class SingleOmpForest(OmpForest):
         forest_predictions = self._base_estimator_predictions(X).T
 
         if self._models_parameters.normalize_D:
+            forest_predictions = forest_predictions.T
             forest_predictions /= self._forest_norms
+            forest_predictions = forest_predictions.T
 
         weights = self._omp.coef_
         omp_trees_indices = np.nonzero(weights)[0]
diff --git a/code/bolsonaro/models/omp_forest_classifier.py b/code/bolsonaro/models/omp_forest_classifier.py
index a51405a6a3278bb86dd52d011b599175bbfc7482..3cb250de23870a707199048eb6842179399a3de6 100644
--- a/code/bolsonaro/models/omp_forest_classifier.py
+++ b/code/bolsonaro/models/omp_forest_classifier.py
@@ -37,7 +37,9 @@ class OmpForestBinaryClassifier(SingleOmpForest):
         forest_predictions = np.array([tree.predict_proba(X) for tree in self._base_forest_estimator.estimators_])
 
         if self._models_parameters.normalize_D:
+            forest_predictions = forest_predictions.T
             forest_predictions /= self._forest_norms
+            forest_predictions = forest_predictions.T
 
         weights = self._omp.coef_
         omp_trees_indices = np.nonzero(weights)
@@ -119,7 +121,9 @@ class OmpForestMulticlassClassifier(OmpForest):
         forest_predictions = np.array([tree.predict_proba(X) for tree in self._base_forest_estimator.estimators_]).T
 
         if self._models_parameters.normalize_D:
+            forest_predictions = forest_predictions.T
             forest_predictions /= self._forest_norms
+            forest_predictions = forest_predictions.T
 
         label_names = []
         preds = []
diff --git a/code/compute_results.py b/code/compute_results.py
index 406f0e0636111add9f3cb6075fe26fd91ff3cf4d..a6eb2f5fb3e6a9326a126fb609614c9d8a8bffcd 100644
--- a/code/compute_results.py
+++ b/code/compute_results.py
@@ -389,7 +389,7 @@ if __name__ == "__main__":
             raise ValueError('Score metrics of all experiments must be the same.')
         experiments_score_metric = base_with_params_experiment_score_metric
 
-        output_path = os.path.join(args.results_dir, args.dataset_name, 'stage4_fix')
+        output_path = os.path.join(args.results_dir, args.dataset_name, 'stage4')
         pathlib.Path(output_path).mkdir(parents=True, exist_ok=True)
 
         Plotter.plot_stage2_losses(