The Learning Mechanism of Bayesian Learning Machine
Jingjing Li · Journal of Gansu Lianhe University · 2009
Bayesian learning is an important research direction in machine learning,which is a probability method of making optimal decision based on prior knowledge,given probability distributions and observed data.Bayesian Theorem is the foundation of this process.Four kinds of Bayesian formulae for different types of parameters and variables are proposed in this paper respectively.The mechanism of information conversion in Bayesian learning is explored to illustrate how to combine the prior,population and sampling information reasonably via an exponential distribution.