Built a tool that takes User input of laptop model and then returns the price of the laptop model based on the data of over 1300 laptop prices.
Data set used is in the laptop_data.csv file Refer to ipynb notebook for detailed information how the model was built. Regression algorithms used:
- Linear regression
- Ridge Regression
- Lasso Regression
- KNN
- Decision Tree
- SVM
- Random Forest
- ExtraTrees
- AdaBoost
- Gradient Boost
- Xg Boost
- Voting regressor
- Stacking
These algorithms were used to compare the R2 scores and MAE of each of them. Turns out random forest gave the best R2 score.