pruning classification is one of the simplest classification algorithms. it works just like if-then. however, when aggregating a lot of prunnings we are able to create a powerful classifier.
the process of bagging based on pruning is really simple but not trivial:
for j=1,…,b,
pick up m samples from a sample set with n samples {(xi,yi)}ni=1. repeating is permitted. then we get a new sample set.
train the pruning classifier ψj with the new sample set.
for all of the pruning classifiers {ψj}bj=1, calculate their average and get f: f(x)←1b∑j=1bψj(x)
