Bayesian network tutorials

Name	Image	Description
Tutorial - A simple model		This tutorial demonstrates building a simple Bayesian network, and calculating some queries.
Tutorial - Mixture model		This tutorial demonstrates building a mixture model of {X,Y} position data.
Tutorial - Time series prediction		This tutorial demonstrates learning a time series model (Dynamic Bayesian network) and making predictions.
Tutorial - Using the Bayes Server API		This tutorial shows how to use the Bayes Server libraries (API) to compile and run one of the help samples.
Tutorial - Classification		This tutorial demonstrates using a Bayesian network for classification. The tutorial demonstrates how to perform batch queries and generate a confusion matrix.
Tutorial - Anomaly detection		This tutorial demonstrates using a Bayesian network for anomaly detection, i.e. detecting data that is unusual or is indicative of a faulty system.
Tutorial - Missing data		This tutorial demonstrates learning a Bayesian network with missing data, performing predictions with missing data, and filling in missing data.
Tutorial - Structural learning		In this tutorial we will build a model from data, adding both nodes and links, and then learning the parameters.
Tutorial - Discovering insight		In this tutorial we use a comparison query to discover insight from a network.
Mixture model interactive demo		This interactive demo models the well known Iris data set with a Mixture Model.