Пример #1
0
        private static void GMNabclassifier_OnPostColonyIteration(object sender, EventArgs e)
        {
            ABCMinerGMN miner = sender as ABCMinerGMN;

            Console.WriteLine("------------------------");
            Console.WriteLine("Iteration [" + miner.CurrentIteration.ToString() + "]");
            Console.WriteLine("------------------------");
            Console.WriteLine("Iteration Best: " + Math.Round(miner.IterationBestQuality, 5).ToString());
            Console.WriteLine("Global Best: " + Math.Round(miner.BestQuality, 5).ToString());
            Console.WriteLine("------------------------");
        }
Пример #2
0
        public static BayesianMultinetClassifier CreateGMNAntBayesianClassification(int seed, int iterations, int colonySize, int convergence, int dependencies, Dataset trainingSet, ISolutionQualityEvaluator <Edge> qualityEvaluator, IHeuristicValueCalculator <Edge> calculator, bool fireEvents)
        {
            DataMining.Utilities.RandomUtility.Initialize(seed);

            CyclicRelationInvalidator  invalidator = new CyclicRelationInvalidator();
            BackwardRemovalLocalSearch localSearch = new BackwardRemovalLocalSearch(qualityEvaluator);

            Problem <Edge> problem = new Problem <Edge>(invalidator, calculator, qualityEvaluator, localSearch);

            ABCMinerGMN mnabcminer = new ABCMinerGMN(iterations, colonySize, convergence, problem, dependencies, trainingSet);

            if (fireEvents)
            {
                mnabcminer.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
                mnabcminer.OnPostColonyIteration        += new EventHandler(GMNabclassifier_OnPostColonyIteration);
            }

            mnabcminer.Work();

            BayesianNetworks.Model.BayesianMultinetClassifier mnbclassifier = mnabcminer.MultinetBayesianClassifier;
            return(mnbclassifier);
        }