Few fixes

code/bolsonaro/trainer.py

@@ -137,6 +137,8 @@ class Trainer(object):
                 y_pred = model.predict(X, extracted_forest_size)
             else:
                 y_pred = model.predict_no_weights(X, extracted_forest_size)
+            y_pred = np.sign(y_pred)
+            y_pred = np.where(y_pred == 0, 1, y_pred)
             result = self._classification_score_metric(y_true, y_pred)
         elif type(model) in [OmpForestBinaryClassifier, OmpForestMulticlassClassifier, RandomForestClassifier]:
             if weights:

code/prepare_models.py

@@ -7,10 +7,12 @@ from tqdm import tqdm
 
 if __name__ == "__main__":
     models_source_path = 'models'
-    models_destination_path = 'bolsonaro_models_27-03-20_v2'
+    models_destination_path = 'bolsonaro_models_29-03-20'
     datasets = ['boston', 'diabetes', 'linnerud', 'breast_cancer', 'california_housing', 'diamonds',
         'steel-plates', 'kr-vs-kp', 'kin8nm', 'spambase', 'gamma', 'lfw_pairs']
 
+    datasets = ['california_housing', 'boston', 'diabetes', 'breast_cancer', 'diamonds', 'steel-plates']
+
     pathlib.Path(models_destination_path).mkdir(parents=True, exist_ok=True)
 
     with tqdm(datasets) as dataset_bar:
@@ -18,12 +20,16 @@ if __name__ == "__main__":
             dataset_bar.set_description(dataset)
             found_paths = glob2.glob(os.path.join(models_source_path, dataset, 'stage5_27-03-20',
                 '**', 'model_raw_results.pickle'), recursive=True)
-            pathlib.Path(os.path.join(models_destination_path, dataset)).mkdir(parents=True, exist_ok=True)
+            #pathlib.Path(os.path.join(models_destination_path, dataset)).mkdir(parents=True, exist_ok=True)
             with tqdm(found_paths) as found_paths_bar:
                 for path in found_paths_bar:
                     found_paths_bar.set_description(path)
                     new_path = path.replace(f'models/{dataset}/stage5_27-03-20/', '')
                     (new_path, filename) = os.path.split(new_path)
+                    if int(new_path.split(os.sep)[0]) != 9:
+                        found_paths_bar.update(1)
+                        found_paths_bar.set_description('Skipping...')
+                        continue
                     new_path = os.path.join(models_destination_path, dataset, new_path)
                     pathlib.Path(new_path).mkdir(parents=True, exist_ok=True)
                     shutil.copyfile(src=path, dst=os.path.join(new_path, filename))