SampleApp.MainForm.btnCreateVectorMachines_Click C# (CSharp) Method

        private void btnCreateVectorMachines_Click(object sender, EventArgs e)
        {
            double[][] inputs;
            int[] outputs;

            getData(out inputs, out outputs);

            int classes = outputs.Distinct().Count();

            var kernel = getKernel();

            // Create the Multi-class Support Vector Machine using the selected Kernel
            ksvm = new MulticlassSupportVectorMachine(inputs[0].Length, kernel, classes);

            // Create the learning algorithm using the machine and the training data
            MulticlassSupportVectorLearning ml = new MulticlassSupportVectorLearning(ksvm, inputs, outputs);

            // Extract training parameters from the interface
            double complexity = (double)numComplexity.Value;
            double tolerance = (double)numTolerance.Value;
            int cacheSize = (int)numCache.Value;
            SelectionStrategy strategy = (SelectionStrategy)cbStrategy.SelectedItem;

            // Configure the learning algorithm
            ml.Algorithm = (svm, classInputs, classOutputs, i, j) =>
            {
                return new SequentialMinimalOptimization(svm, classInputs, classOutputs)
                {
                    Complexity = complexity,
                    Tolerance = tolerance,
                    CacheSize = cacheSize,
                    Strategy = strategy,
                };
            };


            lbStatus.Text = "Training the classifiers. This may take a (very) significant amount of time...";
            Application.DoEvents();

            Stopwatch sw = Stopwatch.StartNew();

            // Train the machines. It should take a while.
            double error = ml.Run();

            sw.Stop();

            lbStatus.Text = String.Format(
                "Training complete ({0}ms, {1}er). Click Classify to test the classifiers.",
                sw.ElapsedMilliseconds, error);

            btnClassifyElimination.Enabled = true;

            // Populate the information tab with the machines
            dgvMachines.Rows.Clear();
            int k = 1;
            for (int i = 0; i < classes; i++)
            {
                for (int j = 0; j < i; j++, k++)
                {
                    var machine = ksvm[i, j];

                    int sv = machine.SupportVectors == null ? 0 : machine.SupportVectors.Length;

                    int c = dgvMachines.Rows.Add(k, i + "-vs-" + j, sv, machine.Threshold);
                    dgvMachines.Rows[c].Tag = machine;
                }
            }

            // approximate size in bytes = 
            //   number of support vectors *
            //   number of doubles in a support vector *
            //   size of double
            int bytes = ksvm.SupportVectorUniqueCount * 1024 * sizeof(double);
            float megabytes = bytes / (1024 * 1024);
            lbSize.Text = String.Format("{0} ({1} MB)", ksvm.SupportVectorUniqueCount, megabytes);
        }