public AffectiveInformation Fuse(IEnumerable <AugmentedAffectiveInformation> affectiveInformation)
{
float score = 0.0f;
float totalWeight = 0.0f;
if (affectiveInformation.Count() == 0)
{
return(null);
}
var result = new AffectiveInformation();
result.Name = affectiveInformation.FirstOrDefault().Name;
if (!this.KalmanFilters.ContainsKey(result.Name))
{
return(null);
}
var kalmanFilter = this.KalmanFilters[result.Name];
kalmanFilter.ProcessObservations(affectiveInformation);
result.Score = (float)System.Math.Round(kalmanFilter.X, 3);
return(result);
}
public AffectiveInformation Fuse(IEnumerable<AugmentedAffectiveInformation> affectiveInformation)
{
if (affectiveInformation.Count() == 0)
{
return null;
}
AffectiveInformation result = new AffectiveInformation();
result.Name = affectiveInformation.FirstOrDefault().Name;
result.Score = affectiveInformation.Select(aff => aff.Score).Max();
return result;
}
public AffectiveInformation Fuse(IEnumerable <AugmentedAffectiveInformation> affectiveInformation)
{
if (affectiveInformation.Count() == 0)
{
return(null);
}
AffectiveInformation result = new AffectiveInformation();
result.Name = affectiveInformation.FirstOrDefault().Name;
result.Score = affectiveInformation.Select(aff => aff.Score).Max();
return(result);
}
public AffectiveInformation Fuse(IEnumerable<AugmentedAffectiveInformation> affectiveInformation)
{
float score = 0.0f;
float totalWeight = 0.0f;
if (affectiveInformation.Count() == 0)
{
return null;
}
AffectiveInformation result = new AffectiveInformation();
result.Name = affectiveInformation.FirstOrDefault().Name;
foreach(var ai in affectiveInformation)
{
score += ai.Classifier.Weight * ai.Score;
totalWeight += ai.Classifier.Weight;
}
result.Score = score / totalWeight;
return result;
}
public AffectiveInformation Fuse(IEnumerable<AugmentedAffectiveInformation> affectiveInformation)
{
float score = 0.0f;
float totalWeight = 0.0f;
if (affectiveInformation.Count() == 0)
{
return null;
}
var result = new AffectiveInformation();
result.Name = affectiveInformation.FirstOrDefault().Name;
if(!this.KalmanFilters.ContainsKey(result.Name))
{
return null;
}
var kalmanFilter = this.KalmanFilters[result.Name];
kalmanFilter.ProcessObservations(affectiveInformation);
result.Score = (float) System.Math.Round(kalmanFilter.X,3);
return result;
}
public AffectiveInformation Fuse(IEnumerable <AugmentedAffectiveInformation> affectiveInformation)
{
float score = 0.0f;
float totalWeight = 0.0f;
if (affectiveInformation.Count() == 0)
{
return(null);
}
AffectiveInformation result = new AffectiveInformation();
result.Name = affectiveInformation.FirstOrDefault().Name;
foreach (var ai in affectiveInformation)
{
score += ai.Classifier.Weight * ai.Score;
totalWeight += ai.Classifier.Weight;
}
result.Score = score / totalWeight;
return(result);
}
public AugmentedAffectiveInformation(AffectiveInformation affectiveInfo, Classifier classifier)
{
this.Name = affectiveInfo.Name;
this.Score = affectiveInfo.Score;
this.Classifier = classifier;
}
public AugmentedAffectiveInformation(AffectiveInformation affectiveInfo, Classifier classifier)
{
this.Name = affectiveInfo.Name;
this.Score = affectiveInfo.Score;
this.Classifier = classifier;
}
