/// <summary>
/// Predicts the specified elements.
/// </summary>
/// <remarks>Use some optimization for RBF kernel</remarks>
/// <param name="elements">The elements.</param>
/// <returns>array of predicted labels</returns>
public override float[] Predict(SparseVec[] elements)
{
if (!IsInitialized)
{
throw new ApplicationException("Evaluator is not initialized. Call init method");
}
float[] predictions = new float[elements.Length];
Parallel.For(0, elements.Length,
i =>
{
//for (int i = 0; i < elements.Length; i++)
//{
float x1Squere = elements[i].DotProduct(); // linKernel.Product(elements[i], elements[i]);//linKernel.DiagonalDotCache[i];
float sum = 0;
int index = -1;
for (int k = 0; k < TrainedModel.SupportElementsIndexes.Length; k++)
{
//support vector squere
float x2Squere = linKernel.DiagonalDotCache[k];
float dot = linKernel.Product(elements[i], TrainedModel.SupportElements[k]);
float rbfVal = (float)Math.Exp(-gamma * (x1Squere + x2Squere - 2 * dot));
index = TrainedModel.SupportElementsIndexes[k];
sum += TrainedModel.Alpha[index] * TrainedModel.Y[k] * rbfVal;
}
sum -= TrainedModel.Bias;
predictions[i] = sum < 0 ? -1 : 1;
}
);
return(predictions);
}
public override float Product(int element1, int element2)
{
if (element1 >= problemElements.Length)
{
throw new IndexOutOfRangeException("element1 out of range");
}
if (element2 >= problemElements.Length)
{
throw new IndexOutOfRangeException("element2 out of range");
}
float x1Squere = 0f, x2Squere = 0f, dot = 0f, prod = 0f;
if (element1 == element2)
{
if (DiagonalDotCacheBuilded)
{
return(DiagonalDotCache[element1]);
}
else
{
//all parts are the same
// x1Squere = x2Squere = dot = linKernel.Product(element1, element1);
//prod = (float)Math.Exp(-Gamma * (x1Squere + x2Squere - 2 * dot));
// (x1Squere + x2Squere - 2 * dot)==0 this expresion is equal zero
//so we can prod set to 1 beceause exp(0)==1
prod = 1f;
}
}
else
{
//when element1 and element2 are different we have to compute all parts
x1Squere = linKernel.Product(element1, element1);
x2Squere = linKernel.Product(element2, element2);
dot = linKernel.Product(element1, element2);
prod = (float)Math.Exp(-Gamma * (x1Squere + x2Squere - 2 * dot));
}
return(prod);
}
