From 5f85fe6603c6fbc68afa71d76c0b51ac8df6a41f Mon Sep 17 00:00:00 2001 From: Biswakalyan Bhuyan Date: Wed, 27 Nov 2024 21:25:26 +0530 Subject: Added prediction feature of year --- main.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/main.py b/main.py index 3355b34..a8bdec8 100644 --- a/main.py +++ b/main.py @@ -17,6 +17,9 @@ def load_data(file_path): # Preprocessing def preprocess_data(df): + # Save the 'Year' column before calculating car age + df['Original_Year'] = df['Year'] + # Calculate Car Age df['Car_Age'] = 2024 - df['Year'] df.drop(columns=['Year'], inplace=True) @@ -42,7 +45,7 @@ def preprocess_data(df): # Train Model def train_model(df, target, model_name): # Features and target - X = df.drop(columns=['Mileage Km/L', 'Price', 'Name']) + X = df.drop(columns=['Mileage Km/L', 'Price', 'Name', 'Original_Year']) y = df[target] # Split data @@ -52,9 +55,7 @@ def train_model(df, target, model_name): categorical_cols = ['Fuel_Type', 'Transmission', 'Owner_Type', 'Location'] numerical_cols = ['Kilometers_Driven', 'Engine CC', 'Power', 'Seats', 'Car_Age'] - preprocessor = ColumnTransformer( - transformers=[ - ('num', StandardScaler(), numerical_cols), + preprocessor = ColumnTransformer( transformers=[ ('num', StandardScaler(), numerical_cols), ('cat', OneHotEncoder(drop='first'), categorical_cols) ] ) @@ -106,5 +107,8 @@ def main(): print("Training price prediction model...") train_model(df, target='Price', model_name='price_predictor') + print("Training year prediction model...") + train_model(df, target='Original_Year', model_name='year_predictor') + if __name__ == "__main__": main() -- cgit v1.2.3-59-g8ed1b