Accord.Statistics.Models.Markov.HiddenMarkovModel.Evaluate C# (CSharp) Метод

        public double Evaluate(int[] observations)
        {
            return Evaluate(observations, false);
        }

        public override void Learn(SequenceData trainingData, SequenceData validationData, SequenceData testData)
        {
            //hmm = SparseHiddenMarkovModel.FromCompleteGraph(2, trainingData.NumSymbols);
            hmm = new HiddenMarkovModel(trainingData.NumSymbols, 4);

            double likelihood = 0.0;
            double newLikelihood = Double.MinValue;

            do
            {
                //HMMGraph graph = hmm.ToGraph();
                HMMGraph graph = ModelConverter.HMM2Graph(hmm);

                //CutEdges(graph, epsilon);

                double[] viterbyScores = ComputeViterbyScores(validationData, true);

                int[] statesToSplit = IdentifyWeakStates(viterbyScores).ToArray();
                foreach (int weakPoint in statesToSplit)
                {
                    SplitState(graph, weakPoint);
                }

                WriteLine(String.Format("Added {0} states", statesToSplit.Length));
                //WriteLine(String.Format("Removed {0} states", RemoveUnpopularStates(graph, viterbyScores)));

                //hmm = SparseHiddenMarkovModel.FromGraph(graph);
                hmm = ModelConverter.Graph2HMM(graph);

                WriteLine("Running Baum Welch...");
                //hmm.Learn(trainingData.GetNonempty(), 0.0, 8);
                hmm.Learn(trainingData.GetNonempty(), 8);

                likelihood = newLikelihood;
                newLikelihood = 0.0;

                foreach (int[] signal in validationData.GetNonempty())
                {
                    newLikelihood += hmm.Evaluate(signal, true);
                }

                WriteLine(String.Empty);
                WriteLine(String.Format("Number of HMM States: {0}", NumberOfStates));
                //WriteLine(String.Format("Transition Sparsity; {0}", hmm.TransitionSparsity));
                WriteLine(String.Format("Log Likelihood: {0}", newLikelihood));
                WriteLine(String.Empty);
            }
            while (Math.Abs(newLikelihood - likelihood) > convergenceThreshold);
        }