fatma-oz / california_housing_prices_ml_models

California_Housing_Prices_Machine Learning_Models

*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.