Seonglae ChoNAM, NODE-GA2M
SIAN (Sparse Interaction Additive Networks)
The core idea of SIAN is the Feature Interaction Selection (FIS) algorithm: it first trains a reference DNN, then applies Archipelago-based interaction detection to measure the interaction strength for each feature subset. Using a heredity condition (threshold $\tau$), it explores higher-order interaction candidates only when lower-order interactions are significant, thereby avoiding an exhaustive search. Based on the selected interaction set , it constructs and trains a GAM-style additive model .
Sparse Interaction Additive Networks via Feature Interaction...
There is currently a large gap in performance between the statistically rigorous methods like linear regression or additive splines and the powerful deep methods using neural networks. Previous...
https://arxiv.org/abs/2209.09326
