feature_interaction
and feature_ratio
parameters within setup. Feature interaction creates new features by multiplying two variables (a * b), while feature ratios create new features but by calculating the ratios of existing features (a / b).polynomial_features
parameter within setup.polynomial_threshold
parameter which uses feature importance based on the combination of Random Forest, AdaBoost and Linear correlation to filter out the non important polynomial features. polynomial_degree
can be used for defining number of degrees to be considered in feature creation.trigonometry_features
parameter within setup.group_features
parameter within setup.bin_numeric_features
parameter within setup. PyCaret uses the โsturgesโ rule to determine the number of bins and also uses K-Means clustering to convert continuous numeric features into categorical features.combine_rare_levels
parameter within setup.create_clusters
parameter within setup.