Create evaluate_model.py

Hedging with Real Estate/Store Sales Prediction/Model/evaluate_model.py

@@ -0,0 +1,13 @@
+import pandas as pd
+from sklearn.metrics import mean_squared_error
+import joblib
+def evaluate_model(df, model):
+    X = df.drop('target', axis=1)
+    y = df['target']
+    predictions = model.predict(X)
+    mse = mean_squared_error(y, predictions)
+    print(f'Mean Squared Error: {mse}')
+if __name__ == "__main__":
+    df = pd.read_csv('path/to/features_data.csv')
+    model = joblib.load('path/to/model.pkl')
+    evaluate_model(df, model)