Marginal likelihood based model comparison in Fuzzy Bayesian Learning

no code implementations • 29 Mar 2017 • Indranil Pan, Dirk Bester

In a recent paper [1] we introduced the Fuzzy Bayesian Learning (FBL) paradigm where expert opinions can be encoded in the form of fuzzy rule bases and the hyper-parameters of the fuzzy sets can be learned from data using a Bayesian approach.

Fuzzy Bayesian Learning

1 code implementation • 28 Oct 2016 • Indranil Pan, Dirk Bester

In this paper we propose a novel approach for learning from data using rule based fuzzy inference systems where the model parameters are estimated using Bayesian inference and Markov Chain Monte Carlo (MCMC) techniques.

Bayesian Inference General Classification +1