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| author |   Biswakalyan Bhuyan <biswa@surgot.in>
| 2024-11-27 16:58:22 +0530 |
|---|---|---|
| committer | Biswakalyan Bhuyan <biswa@surgot.in>
| 2024-11-27 16:58:22 +0530 |
| commit | 9f56376d64bf3307b18cd67d0fe8aaf5a6860f11 (patch) | |
| tree | 515f39ebb936cabe9f5598c6fd784d64dd7eab88 /predict.py | |
| download | autopredict-9f56376d64bf3307b18cd67d0fe8aaf5a6860f11.tar.gz autopredict-9f56376d64bf3307b18cd67d0fe8aaf5a6860f11.tar.bz2 autopredict-9f56376d64bf3307b18cd67d0fe8aaf5a6860f11.zip | |
Data Pridiction of Cars
Diffstat (limited to 'predict.py')
| -rw-r--r-- | predict.py | 26 |
1 files changed, 26 insertions, 0 deletions
diff --git a/predict.py b/predict.py new file mode 100644 index 0000000..6864f9c --- /dev/null +++ b/predict.py @@ -0,0 +1,26 @@ +mport joblib +import pandas as pd + +# Load the model +model = joblib.load('model.pkl') + +# Sample data for prediction +data = { + 'Kilometers_Driven': [50000], + 'Fuel_Type': ['Petrol'], + 'Transmission': ['Manual'], + 'Owner_Type': ['First'], + 'Engine CC': [1197], + 'Power': [82], + 'Seats': [5], + 'Car_Age': [6], + 'Location': ['Mumbai'] +} + +# Convert to DataFrame +input_data = pd.DataFrame(data) + +# Predict +predicted_mileage = model.predict(input_data) + +print(f"Predicted Mileage: {predicted_mileage[0]:.2f} Km/L") |