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.

Conduct MLR using the Karpur Dataset to model and predict permeability in multiple scenario

hw3