Korelacny koeficient

Gesamtmodell

This analysis explores stepwise regression to predict permeability using linear models. The data is cleaned and preprocessed, followed by fitting multiple models with and without log-transformed variables. Models are optimized using backward elimination, and their performance is evaluated using RMSE on both full data and a train-test split. The results highlight the effectiveness of log transformation and stepwise selection in improving prediction accuracy.