CreateModel2() public static method

public static CreateModel2 ( ) : HiddenMarkovModel
return Accord.Statistics.Models.Markov.HiddenMarkovModel
Beispiel #1
0
        public void ComputeTest()
        {
            HiddenMarkovModel hmm = DiscreteHiddenMarkovModelFunctionTest.CreateModel2();

            int states = hmm.States;


            var    function = new MarkovDiscreteFunction(hmm);
            var    target = new ConditionalRandomField <int>(states, function);
            double p1, p2;

            int[] observations, expected, actual;

            observations = new int[] { 0, 0, 1, 1, 1, 2 };
            expected     = hmm.Decode(observations, out p1);
            actual       = target.Compute(observations, out p2);

            Assert.IsTrue(expected.IsEqual(actual));
            Assert.AreEqual(p1, p2, 1e-6);


            observations = new int[] { 0, 1, 2, 2, 2 };
            expected     = hmm.Decode(observations, out p1);
            actual       = target.Compute(observations, out p2);

            Assert.IsTrue(expected.IsEqual(actual));
            Assert.AreEqual(p1, p2, 1e-6);
        }
Beispiel #2
0
        public void LikelihoodTest()
        {
            HiddenMarkovModel hmm = DiscreteHiddenMarkovModelFunctionTest.CreateModel2();

            int states  = hmm.States;
            int symbols = hmm.Symbols;


            var function1 = new MarkovDiscreteFunction(hmm);
            var target1   = new ConditionalRandomField <int>(states, function1);

            var function2 = new MarkovDiscreteFunction(states, symbols);
            var target2   = new ConditionalRandomField <int>(states, function2);


            int[] observations;

            double a, b, la, lb;

            observations = new int[] { 0, 0, 1, 1, 1, 2 };
            a            = target1.LogLikelihood(observations, observations);
            b            = target2.LogLikelihood(observations, observations);
            Assert.IsTrue(a > b);

            observations = new int[] { 0, 0, 1, 1, 1, 2 };
            la           = target1.LogLikelihood(observations, observations);
            lb           = target2.LogLikelihood(observations, observations);
            Assert.IsTrue(la > lb);

            double lla = System.Math.Log(a);
            double llb = System.Math.Log(b);

            Assert.AreEqual(lla, la, 1e-6);
            Assert.AreEqual(llb, lb, 1e-6);
        }
        public void LikelihoodTest()
        {
            var hmm = DiscreteHiddenMarkovModelFunctionTest.CreateModel2();

            int states  = hmm.States;
            int symbols = hmm.Symbols;

            var hcrf = new ConditionalRandomField <int>(states,
                                                        new MarkovDiscreteFunction(hmm));

            var hmm0  = new HiddenMarkovModel(states, symbols);
            var hcrf0 = new ConditionalRandomField <int>(states,
                                                         new MarkovDiscreteFunction(hmm0));


            int[]  observations = new int[] { 0, 0, 1, 1, 1, 2 };
            double la           = hcrf.LogLikelihood(observations, observations);
            double lb           = hcrf0.LogLikelihood(observations, observations);

            Assert.IsTrue(la > lb);

            double lc = hmm.Evaluate(observations, observations);
            double ld = hmm0.Evaluate(observations, observations);

            Assert.IsTrue(lc > ld);

            double za = hcrf.LogPartition(observations);
            double zb = hcrf0.LogPartition(observations);

            la += za;
            lb += zb;

            Assert.AreEqual(la, lc, 1e-6);
            Assert.AreEqual(lb, ld, 1e-6);
        }