By some estimates, about 10% of people in the United States consider themselves “social smokers” who only light up when ...

1 School of Psychology, University of Ottawa, Ottawa, ON, Canada 2 Brain and Mind Research Institute, University of Ottawa, Ottawa, ON, Canada Understanding how functional connectivity between ...

Abstract: In this paper, likelihood-based algorithms are explored for linear digital modulation classification. Hybrid likelihood ratio test (HLRT)- and quasi HLRT (QHLRT)- based algorithms are ...

As of 2.9.1, the log_marginal_likelihood is deprecated. See the docs here. As a matter of fact, I am using it to perform Bayesian model selection on a discrete set of model parameters (e.g. the kernel ...

Calculating the likelihood is a fundamental aspect of statistics and probability theory. It allows us to measure how probable a given set of data is, assuming a specific model or hypothesis.

The log loss function comes under the framework of maximum likelihood. Let’s talk start by talking about loss function. What is a loss function? The term ‘Loss’ refers to the penalty for failing to ...