Abstract: Uplift modeling is a machine learning technique for estimating treatment effects in causal inference problems, where feature selection is crucial for reducing overfitting and computational ...

Abstract: Multilabel causal feature selection has attracted extensive attention in recent years. Current multilabel causal feature selection algorithms typically employ existing Markov Blanket (MB) ...