Category: MCMC

Bayesian Inference Algorithms: MCMC and VI

From: https://towardsdatascience.com/bayesian-inference-algorithms-mcmc-and-vi-a8dad51ad5f5 Unlike other areas of machine learning (ML), Bayesian ML requires us to know when an output is not trustworthy. When you train a regression or xgboost model, the model can be taken at face value given the settings and data. With Bayesian ML, the output is not guaranteed to be correct. Bayesian workflow … Continue reading Bayesian Inference Algorithms: MCMC and VI →

Bayesian Statistics: Analysis of Health Data

From: https://datascienceplus.com/bayesian-statistics-analysis-of-health-data/ The premise of Bayesian statistics is that distributions are based on a personal belief about the shape of such a distribution, rather than the classical assumption which does not take such subjectivity into account. In this regard, Bayesian statistics defines distributions in the following way: Prior: Beliefs about a distribution prior to observing any … Continue reading Bayesian Statistics: Analysis of Health Data →