private double Compute(int k, WeightVector weightVector)
{
double output = 0;
//double secondTerm = 0;
int lineIndex = 0;
//var weightedFeaturesum = new WeightedFeatureSum(weightVector, null, true);
if (_inputSentence.Count != _outputTagsList.Count)
{
throw new Exception("counts dont match "+ _inputSentence.Count + "with "+ _outputTagsList.Count);
}
var ngramTags = new Tags(_tagList);
// first term.
foreach (var sentence in _inputSentence)
{
var outputTags = _outputTagsList[lineIndex];
if (sentence.Count != outputTags.Count)
{
throw new Exception("compute counts dont match " + sentence.Count + "with " + outputTags.Count);
}
output += CalculateGradient(outputTags, k,
ngramTags, lineIndex);
//output += weightedFeaturesum.GetAllFeatureK(outputTags, k, sentence);
//// second term.
//for (var j = 0; j < outputTags.Count; j++)
//{
// double sum = 0;
// foreach (var ngramTag in ngramTags.GetNGramTags(2))
// {
// string[] split = ngramTag.Split(new[] {':'});
// sum += (forwardBackwordAlgos[i].GetQ(j, split[0], split[1]) *
// weightedFeaturesum.GetFeatureK(split[0], split[1], j, k, sentence));
// }
// secondTerm += sum;
//}
lineIndex++;
}
output = output - (_lambda*weightVector.Get(k));
return output;
}
public WeightVector RunIterations(WeightVector weightVector, int iterationCount)
{
for (int iter = 0; iter < iterationCount; iter++)
{
Console.WriteLine(DateTime.Now + " running iteration " + iter);
var newWeightVector = new WeightVector(weightVector.FeatureKDictionary);
SetForwardBackwordAlgo(weightVector);
//for (var k = 0; k < weightVector.FeatureKDictionary.Count; k++)
for (var k = weightVector.FeatureKDictionary.Count-1; k >= 0; k--)
{
if (k%100 == 0)
{
Console.WriteLine(DateTime.Now + " running iteration for k " + k);
}
var wk = Compute(k, weightVector);
wk = weightVector.Get(k) + _lambda*wk;
newWeightVector.SetKey(k, wk);
}
weightVector = newWeightVector;
}
_weightVector = weightVector;
return weightVector;
}
public void ComputeGradientValues(WeightVector weightVector, double[] gradient,
int startIndex, int endIndex )
{
for (var k = startIndex; k < endIndex; k++)
{
double outputDouble = 0;
var kstring = "@#" + k.ToString(CultureInfo.InvariantCulture);
for (var lineIndex = 0; lineIndex < _inputSentence.Count; lineIndex++)
{
var outputTags = _outputTagsList[lineIndex];
double initOutputDouble = 0;
initOutputDouble += GetAllFeatureKFromCache(outputTags, k, lineIndex);
initOutputDouble -= CalculateGradient(outputTags, k,
lineIndex, kstring);
outputDouble += initOutputDouble;
}
gradient[k] = outputDouble - (_lambda * weightVector.Get(k));
}
}
