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Informative Features for Model Comparison
[article]
2018
arXiv
pre-print
Given two candidate models, and a set of target observations, we address the problem of measuring the relative goodness of fit of the two models. We propose two new statistical tests which are nonparametric, computationally efficient (runtime complexity is linear in the sample size), and interpretable. As a unique advantage, our tests can produce a set of examples (informative features) indicating the regions in the data domain where one model fits significantly better than the other. In a
arXiv:1810.11630v1
fatcat:ogsh2onfcrflxms6warz2qdhju