public ArrayList <KeyDat <double, int> > RankFeatures() // Guyon et al. 2002
{
Utils.ThrowException(mModelId == -1 ? new InvalidOperationException() : null);
ArrayList <KeyDat <double, int> > result = new ArrayList <KeyDat <double, int> >();
if (mKernelType != SvmLightKernelType.Linear)
{
// any kernel
int numFeat = SvmLightLib.GetFeatureCount(mModelId);
double allFeat = 0.5 * ComputeCost(-1);
for (int i = 0; i < numFeat; i++)
{
//Console.WriteLine("{0} / {1}", i + 1, numFeat);
double featScore = Math.Abs(allFeat - 0.5 * ComputeCost(/*rmvFeatIdx=*/ i));
result.Add(new KeyDat <double, int>(featScore, i));
}
}
else
{
// linear kernel (fast)
double[] w = GetLinearWeights();
for (int i = 0; i < w.Length; i++)
{
result.Add(new KeyDat <double, int>(0.5 * w[i] * w[i], i));
}
}
result.Sort(DescSort <KeyDat <double, int> > .Instance);
return(result);
}
public double[] GetLinearWeights()
{
Utils.ThrowException(mModelId == -1 ? new InvalidOperationException() : null);
Utils.ThrowException(mKernelType != SvmLightKernelType.Linear ? new InvalidOperationException() : null);
if (mWeights != null)
{
return(mWeights);
}
int featureCount = SvmLightLib.GetFeatureCount(mModelId);
double[] weights = new double[featureCount];
for (int i = 0; i < featureCount; i++)
{
weights[i] = SvmLightLib.GetLinearWeight(mModelId, i);
}
mWeights = weights;
return(weights);
}