Explaining a prediction in some nonlinear models

Autor:	Izzo, Cosimo
Rok vydání:	2019
Předmět:	Computer Science - Machine Learning Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	In this article we will analyse how to compute the contribution of each input value to its aggregate output in some nonlinear models. Regression and classification applications, together with related algorithms for deep neural networks are presented. The proposed approach merges two methods currently present in the literature: integrated gradient and deep Taylor decomposition. Compared to DeepLIFT and Deep SHAP, it provides a natural choice of the reference point peculiar to the model at use. Comment: This paper has been withdrawn by the author as it misses a relevant part of the literature
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1904.09615 Zobrazit plný text záznamu View this record from Arxiv