protected override int Test(FeatureVector vector, out double[] details)
{
// classify(v) = argmax(P(c)P(v|c)) = argmax_c(prob_c * prob_v_c)
double[] v_logProb_c = new double[NoOfClasses];
for (int c_i = 0; c_i < NoOfClasses; c_i++)
{
v_logProb_c[c_i] = CalculateLogProb_v_c(vector, c_i);
}
// Convert back from log to decimal format.
NormalizationHelper.NormalizeLogs(v_logProb_c, 10);
details = v_logProb_c;
return(StatisticsHelper.ArgMax(details));
}
protected override int Test(FeatureVector vector, out double[] details)
{
double[] distribution = new double[NoOfClasses];
// Do two things:
// 1) Calculate the probability of a document belonging to class c_i, given document <c>vector</c>, and
// 2) Calculate Z, which will be used to normalize the distribution shortly.
for (int c_i = 0; c_i < NoOfClasses; c_i++)
{
double logProb = _lambda_c[c_i];
for (int u_i = 0; u_i < vector.UsedFeatures.Length; u_i++)
{
int f_i = vector.UsedFeatures[u_i];
logProb += CalculateLogProb_c_f(c_i, f_i);
}
distribution[c_i] = logProb;
}
NormalizationHelper.NormalizeLogs(distribution, Math.E);
details = distribution;
return(StatisticsHelper.ArgMax(details));
}