ViterbiLearning Class

public class ViterbiLearning : BaseViterbiLearning<int[]>, 
	IUnsupervisedLearning, IConvergenceLearning, IUnsupervisedLearning<HiddenMarkovModel, int[], int[]>

Public Class ViterbiLearning
	Inherits BaseViterbiLearning(Of Integer())
	Implements IUnsupervisedLearning, IConvergenceLearning, IUnsupervisedLearning(Of HiddenMarkovModel, Integer(), Integer())

Accord.Math.Random.Generator.Seed = 0;

// We will try to create a Hidden Markov Model which
//  can detect if a given sequence starts with a zero
//  and has any number of ones after that.
// 
int[][] sequences = new int[][] 
{
    new int[] { 0,1,1,1,1,0,1,1,1,1 },
    new int[] { 0,1,1,1,0,1,1,1,1,1 },
    new int[] { 0,1,1,1,1,1,1,1,1,1 },
    new int[] { 0,1,1,1,1,1         },
    new int[] { 0,1,1,1,1,1,1       },
    new int[] { 0,1,1,1,1,1,1,1,1,1 },
    new int[] { 0,1,1,1,1,1,1,1,1,1 },
};

// Creates a new Hidden Markov Model with 3 states for
//  an output alphabet of two characters (zero and one)
// 
HiddenMarkovModel hmm = new HiddenMarkovModel(new Forward(3), 2);

// Try to fit the model to the data until the difference in
//  the average log-likelihood changes only by as little as 0.0001
// 
var teacher = new ViterbiLearning(hmm)
{
    Tolerance = 0.0001,
    Iterations = 0
};

// Learn the model
teacher.Learn(sequences);

// Calculate the probability that the given
//  sequences originated from the model
// 
double l1; hmm.Decode(new int[] { 0, 1 }, out l1);        // 0.5394
double l2; hmm.Decode(new int[] { 0, 1, 1, 1 }, out l2);  // 0.4485

// Sequences which do not start with zero have much lesser probability.
double l3; hmm.Decode(new int[] { 1, 1 }, out l3);        // 0.0864
double l4; hmm.Decode(new int[] { 1, 0, 0, 0 }, out l4);  // 0.0004

// Sequences which contains few errors have higher probability
//  than the ones which do not start with zero. This shows some
//  of the temporal elasticity and error tolerance of the HMMs.
// 
double l5; hmm.Decode(new int[] { 0, 1, 0, 1, 1, 1, 1, 1, 1 }, out l5); // 0.0154
double l6; hmm.Decode(new int[] { 0, 1, 1, 1, 1, 1, 1, 0, 1 }, out l6); // 0.0154