all AI news
Prediction Errors for Penalized Regressions based on Generalized Approximate Message Passing. (arXiv:2206.12832v2 [stat.ML] UPDATED)
June 30, 2022, 1:11 a.m. | Ayaka Sakata
cs.LG updates on arXiv.org arxiv.org
We discuss the prediction accuracy of assumed statistical models in terms of
prediction errors for the generalized linear model and penalized maximum
likelihood methods. We derive the forms of estimators for the prediction
errors: $C_p$ criterion, information criteria, and leave-one-out cross
validation (LOOCV) error, using the generalized approximate message passing
(GAMP) algorithm and replica method. These estimators coincide with each other
when the number of model parameters is sufficiently small; however, there is a
discrepancy between them in particular in …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Data Analyst (CPS-GfK)
@ GfK | Bucharest
Consultant Data Analytics IT Digital Impulse - H/F
@ Talan | Paris, France
Data Analyst
@ Experian | Mumbai, India
Data Scientist
@ Novo Nordisk | Princeton, NJ, US
Data Architect IV
@ Millennium Corporation | United States