1. A method of training a traffic classifier comprising: generating a training data set comprising a plurality of training flow sets, each training flow set comprising one of a plurality of training feature sets and an associated one of a plurality of class labels, each training feature set and associated class label based on measurements of one of a plurality of training packet flows, the associated class label identifying to which one of a plurality of traffic classes the one of the plurality of training packet flows belongs; training a plurality of binary classifiers using the training data set, each binary classifier associated with one of the plurality of traffic classes, each binary classifier configured to generate an output score based on a training feature set based on measurements of a packet flow; and training a plurality of calibrators using the training data set, each calibrator associated with one of the plurality of binary classifiers, wherein training the plurality of calibrators comprises training each calibrator to translate the output score of the associated binary classifier into a estimated class probability value, the estimated class single probability value indicating a probability that the packet flow on which the output score is based belongs to the traffic class associated with the binary classifier associated with the calibrator.