public void ReMappingFromWeightVector(WeightVector weightVector, bool normalize = true)
{
var newDictKtoF = new Dictionary<int, string>();
var newDictFtoK = new Dictionary<string, int>();
//var weightDict = new Dictionary<int, double>();
//int k = 0;
//var elements = from element in weightVector.WeightArray
// orderby element descending
// where element > 1
// select element;
//var sortedDictionary = from pair in weightVector.WDictionary
// where Math.Abs(pair.Value) > 1
// orderby Math.Abs(pair.Value) descending
// select pair;
const double limit = 0;
var newWeights = new double[weightVector.FeatureCount];
int featureCount = 0;
Array.Clear(newWeights, 0, newWeights.Length);
double max = 0;
for (int i = 0; i < weightVector.FeatureCount; i++)
{
if (max < Math.Abs(weightVector.WeightArray[i]))
{
max = Math.Abs(weightVector.WeightArray[i]);
}
if (Math.Abs(weightVector.WeightArray[i]) > limit)
{
newWeights[featureCount] = weightVector.WeightArray[i];
var feature = DictKToFeatures[i];
newDictFtoK[feature] = featureCount;
newDictKtoF[featureCount] = feature;
featureCount++;
}
}
//if (normalize)
//{
// for (int i = 0; i < featureCount; i++)
// {
// newWeights[i] /= max;
// }
//}
weightVector.WeightArray = newWeights;
weightVector.FeatureCount = featureCount;
DictFeaturesToK = weightVector.FeatureKDictionary = newDictFtoK;
DictKToFeatures = newDictKtoF;
if (normalize)
{
weightVector.AvgNormalize();
}
}
public WeightVector RunIterations(WeightVector weightVector, int iterationCount, int threadCount = 1)
{
_weightVector = weightVector;
for (var iter = 0; iter < iterationCount; iter++)
{
Console.WriteLine(DateTime.Now + " running iteration " + iter);
var newWeightVector = _weightVector.DeepCopy();
SetForwardBackwordAlgo(newWeightVector);
if (threadCount > 1)
{
var doneEvents = new ManualResetEvent[threadCount];
var partition = newWeightVector.FeatureCount / threadCount;
for (int threadIndex = 0; threadIndex < threadCount; threadIndex++)
{
var start = threadIndex*partition;
var end = start + partition;
end = end > newWeightVector.FeatureCount ? newWeightVector.FeatureCount : end;
doneEvents[threadIndex] = new ManualResetEvent(false);
var info = new ThreadInfoObject(this, start, end, newWeightVector,
doneEvents[threadIndex], null);
ThreadPool.QueueUserWorkItem(info.StartGradientComputing, threadIndex);
}
WaitHandle.WaitAll(doneEvents);
}
else
{
ComputeRange(0, _weightVector.FeatureCount, newWeightVector);
}
_weightVector = newWeightVector;
if (iter + 1 < iterationCount)
{
_weightVector.AvgNormalize();
}
}
_weightVector.AvgNormalize();
return _weightVector;
}