In this project we develop an analysis over the house prices. We make a basic EDA to undertand the data. After that we use 3 different linear regression models to try to predict the results.

You should check the EDA and the Model Jupyter notebook to understand the data.

ERROR PREDICTIONS

MAE 1890091.6085735606

MSE 52837100282241.73

RMSE 7268913.280693457

R2 0.7911340192783549

ERROR PREDICTIONS

MAE 994575.8051471912

MSE 168991930773220.47

RMSE 12999689.641419156

R2 0.3319719445910607

ERROR PREDICTIONS

MAE 1381841.2284836913

MSE 36933593916162.945

RMSE 6077301.532437151

R2 0.8540008578505007

ERROR PREDICTIONS

MAE 1267626.8885942616

MSE 122856752785652.98

RMSE 11084076.541852865

R2 0.5143451093686058

1. Alejandro Rodríguez

2. Roger Mesén

3. Coralia Arguedas

4. Luis Rodolfo Valverde Delgado