This project is based on the prediction of GDP of every country in the world Model prediction is created in supervised regression. There are several operations are held in this project which includes:
- Analysing the dataset
- Treating the null values by replacing them by using KNNImputer
- Scaling are done to normalize the data
- Later train_test_split are held to start the modeling with test_size of 30%
- By intial LinearRegression are performed and r2_score for both train and test are shown
- Future selection and cross validation are held to get coefficient of variation value
- By making various Regularisation like Ridge, Lasso, ElasticNet to look though the best model
- At finally Gradient Descent are performed to get better model