A summary of the Feature Selection algorithm is provided in this slide.

![Feature Selection Slide.png](mmF8HPk0WlxR)

On the left, they can find some explanations about the Feature Selection process, along with a link to the analysis where the process took place. Depending on the Feature Selection method chosen, the user can navigate through the models that were trained to obtain the selected features. For instance, when choosing Forward Selection, the analysis contains all the optimal models from 1 selected feature to the set number of features.

On the right, the features are displayed with the height of the bar giving an estimation of their importance. For the Tree selection, it will be the Feature importance coming from the Tree-based model, while for Forward and Lasso selection, it will be the absolute value of the regression coefficient.


