Knowledge Modeling Quick Start Guide
"Bayesian networks are to probability calculus what spreadsheets are for arithmetic"
You can draw upon thousands of pages of documentation to learn about the details of the BayesiaLab software platform, and it may take you years to master it all. However, getting started with BayesiaLab and seeing meaningful results takes little time at all. We are not talking about producing the equivalent of a “Hello World” program; rather, we wish to show you that you can generate insights within a few minutes that would otherwise require laborious calculations. In a way, this guide allows you “to take your first flight” without forcing you through “ground school” beforehand.
All you need for this tutorial is a trial version of BayesiaLab (Win/Mac/Unix), which you can download here: www.bayesia.us/download.
This Quick Start Guide covers a simple example how you can model existing knowledge and then, given new information, compute inference by utilizing Bayes’ rule. The application of the famed Bayes’ rule itself is straightforward and wouldn’t necessarily mandate the use of Bayesian networks. However, the probability calculus required for applying Bayes’ rule would quickly become overwhelming for non-trivial problems. Bayesian networks, plus BayesiaLab’s inference algorithms, can elegantly handle all necessary computations.