Accord.Tests.Statistics.HiddenMarkovModelTest.LearnTest C# (CSharp) Метод

LearnTest() приватный Метод

private LearnTest ( ) : void
Результат void
        public void LearnTest()
        {
            HiddenMarkovModel hmm = new HiddenMarkovModel(2, 3);

            int[] observation = new int[]
            { 
                0,1,1,2,2,1,1,1,0,0,0,0,0,0,0,0,2,2,0,0,1,1,1,2,0,0,
                0,0,0,0,1,2,1,1,1,0,2,0,1,0,2,2,2,0,0,2,0,1,2,2,0,1,
                1,2,2,2,0,0,1,1,2,2,0,0,2,2,0,0,1,0,1,2,0,0,0,0,2,0,
                2,0,1,1,0,1,0,0,0,1,2,1,1,2,0,2,0,2,2,0,0,1
            };

            int[] observation2 = new int[]
            {
                0,1,0,0,2,1,1,0,0,2,1,0,1,1,2,0,1,1,1,0,0,2,0,0,2,1,
                1,1,2,0,2,2,1,0,1,2,0,2,1,0,2,1,1,2,0,1,0,1,1,0,1,2,
                1,0,2,0,1,0,1,2,0,0,2,0,2,0,0,1,0,0,0,0,1,1,2,2,1,2,
                0,1,1,1,2,2,1,1,1,2,2,0,2,1,1,2,0,0,1,1,1,1,1,1,1,0,
                0,1,0,1,0,1,0,0,2,0,1,0,2,0,0,0,0,1,1,1,1,1,1,0,2,0,
                2,2,1,2,1,2,1,0,2,1,1,2,1,2,1,0,0,2,0,0,2,2,2,0,0,1,
                0,1,0,1,0,1,0,0,0,0,0,1,1,1,2,0,0,0,0,0,0,2,2,0,0,0,
                0,0,1,0,2,2,2,2,2,1,2,0,1,0,1,2,2,1,0,1,1,2,1,1,1,2,
                2,2,0,1,1,1,1,2,1,0,1,0,1,1,0,2,2,2,1,1,1,1,0,2,1,0,
                2,1,1,1,2,0,0,1,1,1,1,2,1,1,2,0,0,0,0,0,2,2,2,0,1,1,
                1,0,1,0,0,0,0,2,2,2,2,0,1,1,0,1,2,1,2,1,1,0,0,0,0,2,
                2,1,1,0,1,0,0,0,0,1,0,0,0,2,0,0,0,2,1,2,2,0,0,0,0,0,
                0,2,0,0,2,0,0,0,2,0,1,1,2,2,1,2,1,2,0,0,0,0,2,0,2,0,
                1,0,0,2,2,1,2,1,2,2,0,1,1,1,0,0,1,1,1,2,1,0,0,2,0,0,
                0,0,1,2,0,0,1,2,0,0,0,2,1,1,1,1,1,2,2,0,0,1,1,1,0,0,
                2,0,1,1,0,2,2,0,0,0,1,1,1,1,1,1,2,1,1,0,2,0,0,0,1,1,
                1,2,1,0,0,0,1,1,0,1,1,1,0,0,0,1,1,1,2,2,2,0,2,0,2,1,
                2,1,0,2,1,2,1,0,0,2,1,1,1,1,0,0,0,1,2,0,2,2,1,2,1,1,
                1,0,1,0,0,0,0,2,0,1,1,1,0,2,0,1,0,2,1,2,2,0,2,1,0,0,
                2,1,2,2,0,2,1,2,1,2,0,0,0,1,2,1,2,2,1,0,0,0,1,1,2,0,
                2,1,0,0,0,1,0,0,1,2,0,0,1,2,2,2,0,1,2,0,1,0,1,0,2,2,
                0,2,0,1,1,0,1,1,1,2,2,0,0,0,0,0,1,1,0,0,2,0,0,1,0,0,
                1,0,2,1,1,1,1,1,2,0,0,2,0,1,2,0,1,1,1,2,0,0,0,1,2,0,
                0,0,2,2,1,1,1,0,1,1,0,2,2,0,1,2,2,1,1,1,2,1,0,2,0,0,
                1,1,1,1,1,1,2,1,2,1,0,1,0,2,2,0,1,2,1,1,2,1,0,1,2,1
            };


            var teacher = new BaumWelchLearning(hmm)
            {
                Iterations = 650,
                Tolerance = 0
            };

            double ll = teacher.Run(observation);


            double[] pi = { 1.0, 0.0 };

            double[,] A =
            {
                { 0.7, 0.3 },
                { 0.5, 0.5 }
            };

            double[,] B =
            {
                { 0.6, 0.1, 0.3 },
                { 0.1, 0.7, 0.2 }
            };


            var hmmA = Matrix.Exp(hmm.Transitions);
            var hmmB = Matrix.Exp(hmm.Emissions);
            var hmmP = Matrix.Exp(hmm.Probabilities);


            Assert.IsTrue(Matrix.IsEqual(A, hmmA, atol: 0.1));
            Assert.IsTrue(Matrix.IsEqual(B, hmmB, atol: 0.1));
            Assert.IsTrue(Matrix.IsEqual(pi, hmmP));
        }