Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Willet, Rebecca"'
This paper introduces a novel, computationally-efficient algorithm for predictive inference (PI) that requires no distributional assumptions on the data and can be computed faster than existing bootstrap-type methods for neural networks. Specifically
Externí odkaz:
http://arxiv.org/abs/2306.06582
As opaque predictive models increasingly impact many areas of modern life, interest in quantifying the importance of a given input variable for making a specific prediction has grown. Recently, there has been a proliferation of model-agnostic methods
Externí odkaz:
http://arxiv.org/abs/2207.09097