Infer.NET user guide : Learners

Bayes Point Machine classifiers

This section describes the Infer.NET Bayes Point Machine classifiers and is split into four parts:

The tutorial introduction walks you through a simple binary classification problem, providing a short overview of the Bayes Point Machine and how to use it from C#.

The second section, Learner API, then gives a more detailed description of the binary and multi-class Bayes Point Machine classifiers, showing you how to create a classifier from a data mapping, how to save and load a classifier, how to change its settings, how to train it, how to make predictions, and how to evaluate those predictions.

The third section explains the probabilistic models of the Bayes Point Machine classifiers, explicitly stating the assumptions based on which the models have been constructed.

The final section then introduces the command-line runners, which can be used to train, test and evaluate the Bayes Point Machine classifiers without the need for any implementation.

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