Once all data has been prepared, the user is now asked to select the features (data attributes) to feed into the model creation.
Feature selection is a crucial part of machine learning and a user will typically create many different models using many different combinations of features before finding the best fit.
The user has two options at this point, to either manually select their features or to let Knowi auto-select features for them based upon correlation and information gain algorithms that we run against the dataset.
It is highly recommended to run your model several times with different features selected.
Once the features have been selected, the user then selects the algorithms to run and train their models.