In this respect, Bayesian inference is more intuitive at its core and in closer alignment with our natural mode of probabilistic reasoning than frequentist inference. For example, we are more interested in the probability that 1 treatment is superior to another (Bayesian probability) than in the probability of obtaining certain data assuming the... See more

What is Bayesian Machine Learning?

At its heart, Bayesian Machine Learning is a statistical framework rooted in Bayes’ Theorem , a mathematical principle that describes how to update the probability of a hypothesis as new evidence becomes available.

In machine learning, this translates to modeling not just a single “best” set of parameters but a... See more

Frequentist inference begins by assuming a null hypothesis to be true before data are collected (eg, that there is no effect of a particular treatment on survival). Investigators then collect data, analyze them, and ask, “How surprising is my result if there is actually no effect of the treatment on survival?” The data would be surprising if there... See more