Infer.NET

Tutorials & Examples

Tutorials

The following tutorials provide a step-by-step introduction to Infer.NET. Tutorials and examples can be viewed through the Examples Browser or directly in the Visual Studio project Tutorials.sln. Both of these can be found in the start menu under Infer.NET.

Two coins - a first tutorial, introducing the basics of Infer.NET.
Truncated Gaussian - using variables and observed values to avoid unnecessary compilation.
Learning a Gaussian - using ranges to handle large arrays of data; visualising your model.
Bayes Point Machine - demonstrating how to train and test a Bayes point machine classifer.
Clinical trial - using if blocks for model selection to determine if a new medical treatment is effective.
Mixture of Gaussians - constructing a multivariate mixture of Gaussians.

Examples

Examples of using Infer.NET to solve problems in a variety of real world domains, which will include machine vision, information retrieval, bioinformatics and gaming.

Click model - an information retrieval example which builds a model to reconcile document click counts and human relevance judgements of documents.
Click through model - a web search example where you convert a sequence of clicks by the user into inferences about the relevance of documents.
Image classifier example - an image search example where you classify tagged images by example.
Multi-class classification - a series of examples of using Infer.NET for multi-class classification using a Bayes point machine

Bayes point machine - Perform classification using Multi-class Bayes Point machine
Bayes point machine shared - Perform classification using Multi-class Bayes Point machine when data is available in chunks
Sparse Bayes point machine - Perform classification using multi-class Bayes point machine when data is sparse.

Factor analysis - how to build a low dimensional representation of some data by linearly mapping it into a low dimensional manifold.
Clinical trial UI - the clinical trial tutorial example with an interactive user interface.
Monty Hall problem - an Infer.NET implementation of the Monty Hall problem, along with a graphical user interface.
BayesianPCA - Similar to factor analysis
From the forums:

How-to Guides

How to achieve various tasks in Infer.NET.

How to handle missing data - how to cope with situations where some observations of a variable are missing.
How to represent large irregular graphs - how to represent large graph structures efficiently.

Last modified at 8/3/2009 11:45 AM by John Guiver