//TODO: return érték használatra kívül még nem alkalmas, értelmetlen public override double Train(List <Signature> signatures) { var timeTreshold = TimeFilterClassifier.Train(signatures); var mainThreshold = MainClassifier.Train(signatures); return(timeTreshold + mainThreshold); }
public override double Test(Signature signature) { if (TimeFilterClassifier.Test(signature) < 0.5) { return(0); } else { return(MainClassifier.Test(signature)); } }
public override double Test(Signature signature) { //if (TimeFilterClassifier.Test(signature)<0.5) //TODO: szigorúságot állítani // return 0; //else // return MainClassifier.Test(signature); var timeDecision = TimeFilterClassifier.Test(signature); var mainDecision = MainClassifier.Test(signature); if (timeDecision > 0.4 && mainDecision > 0.5) { return(0.5 * timeDecision + 0.5 * mainDecision); } else { return(0); } }
public override double Test(Signature signature) { var timeDecision = TimeFilterClassifier.Test(signature); // ? 1 : 0; var mainDecision = MainClassifier.Test(signature); // ? 1: 0; var timeClassifierWeight = 1 - MainClassifierWeight; return(timeClassifierWeight * timeDecision + MainClassifierWeight * mainDecision); //return ((MainClassifierWeight * mainDecision) + (timeClassifierWeight * timeDecision)) >= 0.5; //if (timeDecision && mainDecision) return true; //else if (!timeDecision && !mainDecision) return false; //else if (MainClassifierWeight > timeClassifierWeight) return mainDecision; //else if (MainClassifierWeight < timeClassifierWeight) return timeDecision; //else return !timeDecision ? timeDecision : mainDecision; }
//TODO: return még ha használom nem korrekt public override double Train(List <Signature> signatures) { TimeFilterClassifier.Train(signatures); return(MainClassifier.Train(signatures)); }
public CompositeTimeFilterClassifier(IClassifier mainClassifier) { MainClassifier = mainClassifier; TimeFilterClassifier = new TimeFilterClassifier(); }