static IList<double> MergeScores(IList<IList<double>> scores, Dictionary<int, IList<int>> candidates, Dictionary<int, IList<int>> hits)
{
double[] weights;
if (log_reg)
{
var lr = new LogisticRegression();
lr.LearnRate = learn_rate;
lr.NumIter = num_it;
lr.Regularization = regularization;
lr.PredictorVariables = new Matrix<double>(scores);
var targets = new byte[scores[0].Count];
int pos = 0;
foreach (int u in candidates.Keys)
foreach (int i in candidates[u])
targets[pos++] = hits[u].Contains(i) ? (byte) 1 : (byte) 0;
lr.TargetVariables = targets;
lr.Train();
//lr.InitModel();
weights = lr.parameters.ToArray();
/*
for (int i = 0; i < weights.Length; i++)
Console.Error.WriteLine(weights[i]);
*/
}
else
{
weights = new double[scores.Count];
for (int i = 0; i < weights.Length; i++)
weights[i] = 1;
}
return MergeScores(scores, weights);
}
// TODO integrate logistic regression and LIBSVM, maybe later LIBLINEAR
public static void Main(string[] args)
{
var lr = new LogisticRegression();
}
