Improve scripts

.gitignore

@@ -0,0 +1 @@
+scikit-learn/catboost_regressor/catboost_info

scikit-learn/adaboost_regressor/train.py

@@ -17,7 +17,7 @@ X, y = dataset.data, dataset.target
 # Split the dataset into training and testing sets
 X_train, _, y_train, _ = train_test_split(X, y, test_size=0.25, random_state=random_seed)
 
-# Create and train the model
+# Create and train model
 model = AdaBoostRegressor(n_estimators=100, random_state=random_seed)
 model.fit(X_train, y_train)
 

scikit-learn/bayesian_ridge/train.py

@@ -17,7 +17,7 @@ X, y = dataset.data, dataset.target
 # Split the dataset into training and testing sets
 X_train, _, y_train, _ = train_test_split(X, y, test_size=0.25, random_state=random_seed)
 
-# Create and train the Bayesian Ridge Regression model
+# Create and train model
 model = BayesianRidge()
 model.fit(X_train, y_train)
 

scikit-learn/convert2onnx.py

@@ -31,18 +31,19 @@ def prepare_onnx_conversion_params(X, target_opset, model):
 
 
 def convert2onnx(model, initial_type, options, target_opset, onnx_filename):
-    # try:
-    #     model.save_model(onnx_filename, format="onnx")
-    #     print("Model saved in ONNX format successfully.")
-    # except Exception as e:
-    #     print("Error occurred while saving model in ONNX format:", e)
     try:
-        onnx_model = convert_sklearn(model, initial_types=initial_type, options=options, target_opset=target_opset)
-        with open(onnx_filename, "wb") as f:
-            f.write(onnx_model.SerializeToString())
-        print("Model converted to ONNX format and saved successfully.")
+        model.save_model(onnx_filename, format="onnx")
+        print("Model saved in ONNX format successfully.")
     except Exception as e:
-        print("Error occurred while converting model to ONNX format:", e)
+        print("Error occurred while saving model in ONNX format:", e)
+        print("Trying a second method...")
+        try:
+            onnx_model = convert_sklearn(model, initial_types=initial_type, options=options, target_opset=target_opset)
+            with open(onnx_filename, "wb") as f:
+                f.write(onnx_model.SerializeToString())
+            print("Model converted to ONNX format and saved successfully.")
+        except Exception as e:
+            print("Error occurred while converting model to ONNX format:", e)
 
 """
 python convert2onnx.py california adaboost_regressor.joblib adaboost_regressor.onnx