I'm now having some promising results with TMCShapley and KNNShapley. Thanks a lot for the good work. I'm looking for results that translate into incorrect label discovery and deep NN model performance improvements. So what I really care about is whether a datapoint has a positive value or a negative value.
Does anyone have any ideas for adaptations that fulfil this purpose, or other, none DataShapley techniques that already do something similar? e.g. greater accuracy for datapoints near a DataShapley value of 0 by disproportionately sampling from that set.
I'm now having some promising results with TMCShapley and KNNShapley. Thanks a lot for the good work. I'm looking for results that translate into incorrect label discovery and deep NN model performance improvements. So what I really care about is whether a datapoint has a positive value or a negative value.
Does anyone have any ideas for adaptations that fulfil this purpose, or other, none DataShapley techniques that already do something similar? e.g. greater accuracy for datapoints near a DataShapley value of 0 by disproportionately sampling from that set.
Thanks once more.