Algorithm 2 The algorithm for boosting classifier

1:Form a large set of sample features 2:Initialize the weights of training samples 3:for T rounds do: 4:     Normalize the weights of the samples 5:     For available features from the set, train a classifier using a single feature and evaluate the training error 6:     Choose the classifier with the lowest error 7:     Update the weights of the training samples: increase if classified wrongly by this classifier, decrease if correctly 8:end for 9:Form the final strong classifier as the linear combination of the T classifiers.