Industry
251bd0442dfcc53b5a761e050f8022b8-Supplemental.pdf
However, NAMs (likeallGAMs), are not causal models.
NeuralAdditiveModels: InterpretableMachineLearningwithNeuralNets
They perform similarly to existing state-of-the-art generalized additive models in accuracy,but are more flexible because theyare based on neural nets instead ofboosted trees.
Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head Alan Q. Wang Cornell University Minh Nguyen Cornell University Mert R. Sabuncu Cornell University
Machine learning models will often fail when deployed in an environment with a data distribution that is different than the training distribution.
HiBug: On Human-Interpretable Model Debug Muxi Chen, Yu Li, Qiang Xu The Chinese University of Hong Kong
Experimental results demonstrate the efficacy of the HiBug framework.
232eee8ef411a0a316efa298d7be3c2b-Supplemental-Datasets_and_Benchmarks.pdf
Baseline Model As a baseline, we use the aforementioned linear Cox proportional hazard model[Cox72].