Esempio n. 1
0
        /// <summary>
        ///     Run the example.
        /// </summary>
        public void Process()
        {
            // read the iris data from the resources
            Assembly assembly = Assembly.GetExecutingAssembly();
            Stream res = assembly.GetManifestResourceStream("AIFH_Vol2.Resources.iris.csv");

            // did we fail to read the resouce
            if (res == null)
            {
                Console.WriteLine("Can't read iris data from embedded resources.");
                return;
            }

            // load the data
            var istream = new StreamReader(res);
            DataSet ds = DataSet.Load(istream);
            istream.Close();

            IGenerateRandom rnd = new MersenneTwisterGenerateRandom();

            // The following ranges are setup for the Iris data set.  If you wish to normalize other files you will
            // need to modify the below function calls other files.
            ds.NormalizeRange(0, -1, 1);
            ds.NormalizeRange(1, -1, 1);
            ds.NormalizeRange(2, -1, 1);
            ds.NormalizeRange(3, -1, 1);
            IDictionary<string, int> species = ds.EncodeOneOfN(4);

            var particles = new RBFNetwork[ParticleCount];
            for (int i = 0; i < particles.Length; i++)
            {
                particles[i] = new RBFNetwork(4, 4, 3);
                particles[i].Reset(rnd);
            }

            IList<BasicData> trainingData = ds.ExtractSupervised(0, 4, 4, 3);

            IScoreFunction score = new ScoreRegressionData(trainingData);

            var train = new TrainPSO(particles, score);

            PerformIterations(train, 100000, 0.05, true);

            var winner = (RBFNetwork) train.BestParticle;

            QueryOneOfN(winner, trainingData, species);
        }
Esempio n. 2
0
        /// <summary>
        ///     Run the example.
        /// </summary>
        public void Process()
        {
            // read the iris data from the resources
            Assembly assembly = Assembly.GetExecutingAssembly();
            Stream res = assembly.GetManifestResourceStream("AIFH_Vol2.Resources.iris.csv");

            // did we fail to read the resouce
            if (res == null)
            {
                Console.WriteLine("Can't read iris data from embedded resources.");
                return;
            }

            // load the data
            var istream = new StreamReader(res);
            DataSet ds = DataSet.Load(istream);
            istream.Close();

            IGenerateRandom rnd = new MersenneTwisterGenerateRandom();


            // The following ranges are setup for the Iris data set.  If you wish to normalize other files you will
            // need to modify the below function calls other files.
            ds.NormalizeRange(0, -1, 1);
            ds.NormalizeRange(1, -1, 1);
            ds.NormalizeRange(2, -1, 1);
            ds.NormalizeRange(3, -1, 1);
            IDictionary<string, int> species = ds.EncodeOneOfN(4);
            istream.Close();

            var codec = new RBFNetworkGenomeCODEC(4, RbfCount, 3);

            IList<BasicData> trainingData = ds.ExtractSupervised(0,
                codec.InputCount, 4, codec.OutputCount);

            IPopulation pop = InitPopulation(rnd, codec);

            IScoreFunction score = new ScoreRegressionData(trainingData);

            var genetic = new BasicEA(pop, score) {CODEC = codec};
            genetic.AddOperation(0.7, new Splice(codec.Size/3));
            genetic.AddOperation(0.3, new MutatePerturb(0.1));


            PerformIterations(genetic, 100000, 0.05, true);

            var winner = (RBFNetwork) codec.Decode(genetic.BestGenome);

            QueryOneOfN(winner, trainingData, species);
        }
        /// <summary>
        ///     Run the example.
        /// </summary>
        public void Process()
        {
            // read the iris data from the resources
            Assembly assembly = Assembly.GetExecutingAssembly();
            Stream res = assembly.GetManifestResourceStream("AIFH_Vol2.Resources.iris.csv");

            // did we fail to read the resouce
            if (res == null)
            {
                Console.WriteLine("Can't read iris data from embedded resources.");
                return;
            }

            // load the data
            var istream = new StreamReader(res);
            DataSet ds = DataSet.Load(istream);
            istream.Close();

            // The following ranges are setup for the Iris data set.  If you wish to normalize other files you will
            // need to modify the below function calls other files.
            ds.NormalizeRange(0, -1, 1);
            ds.NormalizeRange(1, -1, 1);
            ds.NormalizeRange(2, -1, 1);
            ds.NormalizeRange(3, -1, 1);
            IDictionary<string, int> species = ds.EncodeOneOfN(4);
            istream.Close();

            var network = new RBFNetwork(4, 4, 3);

            IList<BasicData> trainingData = ds.ExtractSupervised(0, 4, 4, 3);

            IScoreFunction score = new ScoreRegressionData(trainingData);

            var train = new ContinuousACO(network, score, 30);

            PerformIterations(train, 100000, 0.05, true);

            train.FinishTraining();

            QueryOneOfN(network, trainingData, species);
        }