/*********************************
* Function: getStrongClassifier
* -----------------------------
* This function generates a strong classifier that can accurately distinguish
* positive training examples from negative training examples
*
* td: set of feature vectors
* num_classifiers: the number of weak classifiers we want to be in the strong
* classifier (20 tends to be a good default it seems)
*
* returns: a strong classifier -- set of weak classifiers in optimal order
*/
StrongClassifier AdaBooster::getStrongClassifier(const TrainingData &trainingData, unsigned int num_classifiers){
TrainingData td = trainingData;
// set dimensions and number of features
dimensions = td.dimensions();
num_features = td.size();
// initialize feature weights
init_feature_weight(td);
// vector of weak classifiers that make up a strong classifier
vector<WeakClassifier> strong_classifier;
// sort circle by features -- store in *sorted*
create_feature_views(td);
//td.printData();
//char garbage[80]; // use this with cin.getline() below
for (unsigned int i=0; i<num_classifiers; i++){
// indentify best classifier
WeakClassifier *wc = get_best_classifier();
// if index invalid, then we're done constructing our strong classifier
if (!wc)
return StrongClassifier(strong_classifier);
// otherwise, add best classifier to strong_classifier
strong_classifier.push_back(*wc);
//strong_classifier.back().printClassifier();
// don't need classifier anymore so delete it
delete wc;
// don't think this is useful anymore, but I'm scared to delete it
// without more testing, so it stays for now. TODO: delete this?
td.writeData(tdFile);
//td.printData();
// update weights of features
update_feature_weight(td, strong_classifier.back());
// print out status update
printf("\rClassifiers Calculated: %d ", i+1);
fflush(stdout);
/*
td.printData(); // prints out the set of training data
cin.getline(garbage, 80); // if you want to pause printing, use this
// */
}
// delete sorted array
delete [] sorted;
// StrongClassifier error reporting
/*vector< vector<double> > strong_err = getStrongError(td, strong_classifier);
printStrongStats(strong_err);*/
return strong_classifier;
}
