Esempio n. 1
0
        public void Run()
        {
            if (D == null)
            {
                throw new InvalidOperationException("Run ConfigureEvolver() first");
            }
            if (_validate)
            {
                D.VerifyOutput();
            }


            if (_outputBaseline)
            {
                //Run a simulation including all features to find the best combination of parameters for the particular classifier
                T      baseline = new T();
                string basePath = OptoGlobals.EnvironmentTag + "/" + OptoGlobals.DataSetName + "/" + baseline.GetToken + "Baseline";
                EvoOptimizerProgram <T> baseProgram = new EvoOptimizerProgram <T>();
                baseProgram.MaxGen             = 100;
                baseProgram.SaveAfterGens      = 25;
                baseProgram.PopSize            = 50;
                baseProgram.IncludeAllFeatures = true;
                baseProgram.OutputFileStem     = basePath;
                baseProgram.Noload             = true;
                baseProgram._outputBaseline    = false;
                baseProgram.ConfigureAndRun();
            }

            Stopwatch sw = new Stopwatch();

            _running = true;
            for (int x = 0; x < _maxGen; ++x)
            {
                sw.Start();
                D.AdvanceGeneration();
                Debug.WriteLine("Elapsed time for generation " + x + " = " + sw.ElapsedMilliseconds + "  ms");
                Console.WriteLine("Elapsed time for generation " + x + " = " + sw.ElapsedMilliseconds + "  ms");

                double sum = 0, count = 0;
                foreach (T t in D.Population)
                {
                    sum   += t.Fitness;
                    count += 1;
                }
                Console.WriteLine("Best Fitness = " + D.Population[0].Fitness + " \n Average fitness = " + D.AverageFitness);
                if (x % _saveAfterGens == 0)
                {
                    D.DumpLookupToFile(OutputFileStem);
                }
                sw.Reset();
            }
            D.DumpLookupToFile(OutputFileStem);
            OutputFileStem = null;
            //Console.ReadLine();
        }
Esempio n. 2
0
        static void Main(string[] args)
        {
            string compTagFile = @"..\..\compTag.txt";

            if (System.IO.File.Exists(compTagFile))
            {
                OptoGlobals.LoadTagFromFile(compTagFile);
            }
            else
            {
                using (System.IO.StreamWriter fout = new System.IO.StreamWriter(compTagFile)){
                    fout.WriteLine("NoTag");
                }
            }

            OptoGlobals.IsDebugMode = false;
            // Create the MATLAB instance
            String GlobalPath = "../../../Data/Hackathon/DataSetConfigSquish.csv";
            int    maxGen = 100, saveAfterGens = 25, popSize = 50, baseCompUB = 10, maxComp = 2000;

            if (args.Length >= 2)
            {
                GlobalPath = args[1];
            }
            for (int i = 2; i < args.Length; ++i)
            {
                switch (args[i].ToLower())
                {
                case "path":
                case "-p":
                    GlobalPath = args[++i];
                    break;

                case "gen":
                case "-g":
                    maxGen = Int32.Parse(args[++i]);
                    break;

                case "save":
                case "-r":
                    saveAfterGens = Int32.Parse(args[++i]);
                    break;

                case "population":
                case "-pop":
                    saveAfterGens = Int32.Parse(args[++i]);
                    break;

                case "compub":
                case "-c":
                    baseCompUB = Int32.Parse(args[++i]);
                    break;

                case "maxcomp":
                case "-m":
                    maxComp = Int32.Parse(args[++i]);
                    break;
                }
            }

            OptoGlobals.ConfigureForDataset(GlobalPath);
            double[] poot = { OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(),
                              OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble(), OptoGlobals.RNG.NextDouble() };
            object   pootwrap = poot;
            //Hunter x = new Hunter();
            double   nerp;
            Daedalus D = new Daedalus();

            //x.Vote(pootwrap, out nerp);
            CTreeOptimizer.CTreeOptimizer.RewriteBitLengths();
            EvoOptimizerProgram <CTreeOptimizer.CTreeOptimizer> decisionTreeProgram = new EvoOptimizerProgram <CTreeOptimizer.CTreeOptimizer>();

            decisionTreeProgram.MaxGen         = maxGen;
            decisionTreeProgram.SaveAfterGens  = saveAfterGens;
            decisionTreeProgram.PopSize        = popSize;
            decisionTreeProgram.OutputBaseline = false;
            MulticlassNBOptimizer.MulticlassNBOptimizer.RewriteBits();
            EvoOptimizerProgram <MulticlassNBOptimizer.MulticlassNBOptimizer> naiveBayesProgram = new EvoOptimizerProgram <MulticlassNBOptimizer.MulticlassNBOptimizer>();

            naiveBayesProgram.MaxGen         = maxGen;
            naiveBayesProgram.SaveAfterGens  = saveAfterGens;
            naiveBayesProgram.PopSize        = popSize;
            naiveBayesProgram.OutputBaseline = false;

            //Configure the program here- set things like multi-threading, etc, if desired

            D.MaxGen         = maxGen * 10;
            D.RecordInterval = saveAfterGens;
            D.PopSize        = popSize * 10;
            D.InitialComplexityUpperBound = baseCompUB;
            D.MaxCellComplexity           = maxComp;
            D.ConfigureCellDelegatesForDatabase();

            //System.Threading.Thread t = new System.Threading.Thread(() => D.Run());
            //t.Start();
            //D.Run();

            naiveBayesProgram.ConfigureAndRun();

            decisionTreeProgram.ConfigureAndRun();

            /*MulticlassNBOptimizer.MulticlassNBOptimizer bestNb = new MulticlassNBOptimizer.MulticlassNBOptimizer("1101110111010101001010100000101111000111000010101110101011011111111100011011100");
             * bestNb.Eval();
             *
             * OptoGlobals.readInSpecialTestSet();
             *
             * bestNb.Eval();
             * using(StreamWriter fout = new StreamWriter(new FileStream("mysubmission.csv", FileMode.Create))){
             *  bestNb.DumpLabelsToStream(fout);
             * }
             * SerializationChecks();
             */
        }