Fig. 4From: Large sample size and nonlinear sparse models outline epistatic effects in inflammatory bowel diseaseComparison of four sparsification methods: A based on biological pathways (KEGG), B randomly, C learned using RigL algorithm, and D learned using heavy \(\text {L}_1\) regularization. For fair comparison, all models shown have the same number of connections and hidden unitsBack to article page