static void Main(string[] args)
{
// read the arguments and stick them into the config manager
ConfigManager.Instance.ParseArguments(args);
// next need to get the file name and read the elements into dense training data
ITrainingData trainingData = new DenseTrainingData();
// initialize the dot product kernel, stick it in the SVM algorithm
// TODO: use the arguments to determine the kernel to use
// 1) dot product
// 2) radial basis function kernel
// 3) polynomial kernel (how to specify the degree of polynomial)
IKernel kernel = new DotProductKernel();
ISVMAlgorithm svm = new SMOSVMAlgorithm(trainingData, kernel);
// SVM algorithm run
CalculationStore data = svm.run();
// print the weight vectors and 'b' constants
data.Print();
// record the results of the SVM run
CalculationStore.RecordResults();
}
static public SMOStep Instance(SMOSVMAlgorithm alg)
{
if(smoStep == null)
{
smoStep = new SMOStep(alg);
}
return smoStep;
}
private SMOStep(SMOSVMAlgorithm alg)
{
this.alg = alg;
C = ConfigManager.Instance.C;
epsilon = ConfigManager.Instance.epsilon;
}
