/// <summary>
/// Learns the parameters for the given system.
/// </summary>
/// <param name="initial">The initial.</param>
/// <param name="transition">The transition.</param>
/// <param name="emission">The emission.</param>
/// <param name="trainingSet">The training set.</param>
public void Learn([NotNull] InitialStateMatrix initial, [NotNull] TransitionMatrix transition,
[NotNull] EmissionMatrix emission,
[NotNull] IList <IList <LabeledObservation> > trainingSet)
{
Learn(initial, trainingSet);
Learn(transition, trainingSet);
Learn(emission, trainingSet);
}
/// <summary>
/// Initializes a new instance of the <see cref="HiddenMarkovModel" /> class.
/// </summary>
/// <param name="states">The states.</param>
/// <param name="inital">The inital state matrix.</param>
/// <param name="transition">The transmission matrix.</param>
/// <param name="emission">The emission matrix.</param>
public HiddenMarkovModel(
[NotNull] ReadOnlyCollection <IState> states,
[NotNull] InitialStateMatrix inital,
[NotNull] TransitionMatrix transition,
[NotNull] EmissionMatrix emission)
{
_states = states;
_inital = inital;
_transition = transition;
_emission = emission;
}
/// <summary>
/// Learns the emission probabilities from the specified training set.
/// </summary>
/// <param name="emission">The emission.</param>
/// <param name="trainingSet">The training set.</param>
private void Learn([NotNull] EmissionMatrix emission, [NotNull] IEnumerable <IList <LabeledObservation> > trainingSet)
{
var observationsGroupedByState = trainingSet
.SelectMany(set => set)
.GroupBy(set => set.State);
foreach (var example in observationsGroupedByState)
{
var state = example.Key;
var examples = example.GroupBy(e => e.Observation).ToList();
var totalCount = examples.Sum(e => e.Count());
foreach (var group in examples)
{
var observation = group.Key;
var count = group.Count();
var probability = (double)count / totalCount;
emission.SetEmission(state, observation, probability);
}
}
}
