float StrongClassifier::evaluate(const std::vector<float> &features) const { //feature
float decision = 0;
for (int i=0; i<m_weakClassifiers.size(); i++) {
WeakClassifier weak = m_weakClassifiers.at(i);
int sign;
if ( (weak.threshold() > features[weak.dimension()] && !weak.isFlipped()) ||
(weak.threshold() < features[weak.dimension()] && weak.isFlipped()) )
sign = 1;
else
sign = -1;
decision += weak.weight() * sign;
}
return decision;
}
/**************************************
* Fucntion: is_classifier_correct
* -------------------------------
* returns true if weak classifier (wc) correctly identified the
* feature vector (fv), false otherwise.
*/
bool AdaBooster::is_classifier_correct(WeakClassifier &wc, FeatureVector &fv){
// check if threshold is greater than (or equal to) feature
bool guess = ( wc.threshold() >= fv.at(wc.dimension()) );
// if classifier is flipped, negate guess
guess = wc.isFlipped() ? !guess : guess;
// find actual value of point
bool real = ( fv.val() == POS );
// return if guess and real agree
return ( real == guess );
}