Infer.NET user guide : Learners : Bayes Point Machine classifiers : Command-line runners

Training

A Bayes Point Machine is trained using the Train module, both in binary and multi-class classification. The Train module reads a training set and returns a serialized trained classifier, which can then be used to make predictions or train incrementally.

The Train module has the following command-line arguments:

Required arguments

• training-set: The file with training data containing ground truth labels and features in the format described earlier.
• model: The file to which the trained Bayes Point Machine classifier will be saved.

Optional arguments

• iterations: The number of training algorithm iterations (defaults to 30).
• batches: The number of batches into which the training data is split (defaults to 1).
• compute-evidence: If specified, the Bayes Point Machine classifier will compute model evidence on the training data (defaults to false).

For more information about the command-line arguments, see Settings. A more detailed explanation of training is available here.

Example

Learner Classifier BinaryBayesPointMachine Train   
    --training-set training-set.dat --model trained-binary-bpm.bin   
    --iterations 25 --batches 2 --compute-evidence  

Learner Classifier MulticlassBayesPointMachine Train   
    --training-set training-set.dat --model trained-multiclass-bpm.bin   
    --iterations 25 --batches 2 --compute-evidence