The objective of the project is to perform advance regression techniques to predict the house prices in Boston.
- train.csv - the training set
- test.csv - the test set
- data_description.txt - full description of each column, originally prepared by Dean De Cock but lightly edited to match the column names used here
- sample_submission.csv - a benchmark submission from a linear regression on year and month of sale, lot square footage, and number of bedrooms
All the required libraries are included in the file requirements.txt
- Machine Learning
- LazyPredict
- GradientBoostingRegressor
- XGBRegressor
- LGBMRegressor
- StackingRegressor
- Lasso
- Ridge
- Optuna
Made With ❤️ by Sidharth kumar mohanty
Any issues??? Feel free to ask.Linkedin
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