PASS-GLM: Polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Generalized linear models (GLMs) - such as logistic regression, Poisson regression, and robust regression - provide interpretable models for diverse data types. Probabilistic approaches, particularly Bayesian ones, allow coherent estimates of uncertainty, incorporation of prior information, and shar...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://hdl.handle.net/1721.1/128777 |