public ArrayList <IdxDat <double> > GetAlphas() // returns pairs (support vector index, alpha * y)
{
Utils.ThrowException(mModelId == -1 ? new InvalidOperationException() : null);
ArrayList <IdxDat <double> > alphas = new ArrayList <IdxDat <double> >();
for (int i = 0; i < SvmLightLib.GetSupportVectorCount(mModelId); i++)
{
double alpha = SvmLightLib.GetSupportVectorAlpha(mModelId, i);
int idx = SvmLightLib.GetSupportVectorIndex(mModelId, i);
alphas.Add(new IdxDat <double>(idx, alpha));
}
return(alphas);
}
private double[][] GetKernel(int rmvFeatIdx)
{
int numSv = SvmLightLib.GetSupportVectorCount(mModelId);
// initialize matrix
double[][] kernel = new double[numSv][];
// compute linear kernel
SparseMatrix <double> m = new SparseMatrix <double>();
for (int i = 0; i < numSv; i++)
{
SparseVector <double> sv = GetSupportVector(i);
m[i] = sv;
}
if (rmvFeatIdx >= 0)
{
m.RemoveColAt(rmvFeatIdx);
}
SparseMatrix <double> mTr = m.GetTransposedCopy();
for (int i = 0; i < numSv; i++)
{
double[] innerProd = ModelUtils.GetDotProductSimilarity(mTr, numSv, m[i]);
kernel[i] = innerProd;
}
// compute non-linear kernel
switch (mKernelType)
{
case SvmLightKernelType.Polynomial:
for (int row = 0; row < kernel.Length; row++)
{
for (int col = 0; col < kernel.Length; col++)
{
kernel[row][col] = Math.Pow(mKernelParamS * kernel[row][col] + mKernelParamC, mKernelParamD);
}
}
break;
case SvmLightKernelType.RadialBasisFunction:
double[] diag = new double[kernel.Length];
for (int i = 0; i < kernel.Length; i++)
{
diag[i] = kernel[i][i];
} // save diagonal
for (int row = 0; row < kernel.Length; row++)
{
for (int col = 0; col < kernel.Length; col++)
{
kernel[row][col] = Math.Exp(-mKernelParamGamma * (diag[row] + diag[col] - 2.0 * kernel[row][col]));
}
}
break;
case SvmLightKernelType.Sigmoid:
for (int row = 0; row < kernel.Length; row++)
{
for (int col = 0; col < kernel.Length; col++)
{
kernel[row][col] = Math.Tanh(mKernelParamS * kernel[row][col] + mKernelParamC);
}
}
break;
}
return(kernel);
}
