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; }