public void SigmoidPrimeTest()
{
var a = new Matrix(2, 2);
a.InRandomize();
var b = a.Duplicate();
a = new SigmoidKernel().Backward(a);
b.InMap((x) => 1.0 / (1 + Math.Exp(-x)) * (1 - 1.0 / (1 + Math.Exp(-x))));
Assert.IsTrue(a == b, "Sigmoid Derivative successful");
}
public void SigmoidTest()
{
var a = new Matrix(2, 2);
a.InRandomize();
var b = a.Duplicate();
a = new SigmoidKernel().Forward(a);
b.InMap((x) => 1.0 / (1 + Math.Exp(-x)));
Assert.IsTrue(a == b, "Sigmoid Activation successful");
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int size_cache = 10;
double gamma = 1.2;
double coef0 = 1.3;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
SigmoidKernel kernel = new SigmoidKernel(feats_train, feats_test, size_cache, gamma, coef0);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
// Parse and Display km_train
Console.Write("km_train:\n");
int numRows = km_train.GetLength(0);
int numCols = km_train.GetLength(1);
for (int i = 0; i < numRows; i++)
{
for (int j = 0; j < numCols; j++)
{
Console.Write(km_train[i, j] + " ");
}
Console.Write("\n");
}
// Parse and Display km_test
Console.Write("\nkm_test:\n");
numRows = km_test.GetLength(0);
numCols = km_test.GetLength(1);
for (int i = 0; i < numRows; i++)
{
for (int j = 0; j < numCols; j++)
{
Console.Write(km_test[i, j] + " ");
}
Console.Write("\n");
}
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
int size_cache = 10;
double gamma = 1.2;
double coef0 = 1.3;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
SigmoidKernel kernel = new SigmoidKernel(feats_train, feats_test, size_cache, gamma, coef0);
double[,] km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
double[,] km_test = kernel.get_kernel_matrix();
// Parse and Display km_train
Console.Write("km_train:\n");
int numRows = km_train.GetLength(0);
int numCols = km_train.GetLength(1);
for(int i = 0; i < numRows; i++){
for(int j = 0; j < numCols; j++){
Console.Write(km_train[i,j] +" ");
}
Console.Write("\n");
}
// Parse and Display km_test
Console.Write("\nkm_test:\n");
numRows = km_test.GetLength(0);
numCols = km_test.GetLength(1);
for(int i = 0; i < numRows; i++){
for(int j = 0; j < numCols; j++){
Console.Write(km_test[i,j] +" ");
}
Console.Write("\n");
}
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
int size_cache = 10;
double gamma = 1.2;
double coef0 = 1.3;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
SigmoidKernel kernel = new SigmoidKernel(feats_train, feats_test, size_cache, gamma, coef0);
DoubleMatrix km_train = kernel.get_kernel_matrix();
kernel.init(feats_train, feats_test);
DoubleMatrix km_test = kernel.get_kernel_matrix();
Console.WriteLine(km_train.ToString());
Console.WriteLine(km_test.ToString());
modshogun.exit_shogun();
}
internal static HandleRef getCPtr(SigmoidKernel obj)
{
return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr);
}
internal static HandleRef getCPtr(SigmoidKernel obj) {
return (obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr;
}