*CALIFORNIA HOUSE PRICE data was used in this study.
*Since the data is clean, no preprocessing is required.
*The aim is to experience the regression models available in the sklearn library.
*The models used are:
- LinearRegression
- Ridge Regression
- KernelRidge Regression
- GaussianProcess Regression
- SVR (Support vector regression)
- DecisionTree Regression
- PLS Regression
- AdaBoost Regression
- KNeighbors Regression
- MLP Regression
- RandomForest Regression
- XGBoost Regression
*MAE, R2, MSE values were examined.
*R2 and MAE values were visualized with the plt function from the matplotlib library.