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2020 25th International Conference on Pattern Recognition (ICPR)
Shapley values are great analytical tools in game theory to measure the importance of a player in a game. Due to their axiomatic and desirable properties such as efficiency, they have become popular for feature importance analysis in data science and machine learning. However, the time complexity to compute Shapley values based on the original formula is exponential, and as the number of features increases, this becomes infeasible. Castro et al.  developed a sampling algorithm, to estimatedoi:10.1109/icpr48806.2021.9412511 fatcat:dwvzbkcaznhgdcklb6ckamwgmq