private static ContinuousHiddenMarkovModel TrainHelper(double[][] sequences)
{
var hmm = new ContinuousHiddenMarkovModel(States, Symbols);
var learner = new ContinuousBaumWelchLearning(hmm)
{
Tolerance = MinTolerance,
Iterations = MaxIterations,
FittingOptions = new NormalOptions()
{
Regularization = RegularisationFactor
}
};
learner.Run(sequences);
return hmm;
}
/// <summary>
/// Train this current Hidden Markov Model using the provided sequences.
///
/// A subset of the features can be selected by the selectFeatures function.
/// </summary>
/// <param name="sequences">The set of training examples</param>
/// <param name="selectFeatures">
/// A (function: Seq -> double[][]) which selects the relevant features from the sequence.
/// </param>
public void Train(IList<Sequence> sequences, Func<Sequence, double[][]> selectFeatures)
{
var learner = new ContinuousBaumWelchLearning(CHMM)
{
Tolerance = MinTolerance,
Iterations = MaxIterations,
// This is necessary to prevent overfitting:
FittingOptions = new NormalOptions {Regularization = RegularisationFactor}
};
learner.Run(sequences.Select(selectFeatures).ToArray());
}
