//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));
}
