regression model package from Train In Data.
Project description
CAR PRICE PREDICTION
A machine learning program that predicts the price of cars as seen in the dataset given. This program uses a simple ensemble regressor algorithm to predict a reasonable Manufacturer suggested retail price for cars.
Data set and its description
Data | Description |
---|---|
Make | Company or brand name |
Model | Car category |
Year | Production year |
Engine fuel type | Engine fuel combustion type |
Engine HP | Horse power capability of the engine |
Engine cylinders | Number of cylinders |
Transmission type | Automatic, manual etc |
Driven_wheels | type of wheel drive |
Number of doors | Available doors attached to the car |
Market_category | Targeted audience for the car |
Vehicle size | dimension of the car |
Vehicle style | car design appeal |
Highway MPG | Highway miles travelled |
City MPG | City miles attainable |
Popularity | Numeric figure |
MSRP | Manufacturers' recommended pricing |
Dependencies and packages
- numpy>=1.20.0,<1.21.0
- pandas>=1.3.5,<1.4.0
- pydantic>=1.8.1,<1.9.0
- scikit-learn>=1.0.2,<1.1.0
- strictyaml>=1.3.2,<1.4.0
- ruamel.yaml==0.16.12
- feature-engine>=1.0.2,<1.1.0
- joblib>=1.0.1
Source code link
Source code link: Github link
Project details
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