Hello,
Since DeepLift outputs different contribution scores for each input data, what is the suggested way to aggregate the DeepLift outputs? For example, with input neurons A and B, samples s1 and s2, DeepLift outputs contribution scores c11, c12 for s1 and c21, c22 for s2. One way to aggregate is to calculate the mean (contribution of A = (c11+c21)/2) and (contribution of B = (c12+c22)/2). Maybe median is another option. Or is it not plausible to aggregate DeepLift outputs for different samples? Thanks.
Hello,
Since DeepLift outputs different contribution scores for each input data, what is the suggested way to aggregate the DeepLift outputs? For example, with input neurons A and B, samples s1 and s2, DeepLift outputs contribution scores c11, c12 for s1 and c21, c22 for s2. One way to aggregate is to calculate the mean (contribution of A = (c11+c21)/2) and (contribution of B = (c12+c22)/2). Maybe median is another option. Or is it not plausible to aggregate DeepLift outputs for different samples? Thanks.