Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier

Algorithm 1 AdaBoost.

	Input: Dataset,
	The weight of each sample in the training set constitutes a weight vector,
	The base learning algorithm,
	Number of learning rounds,
	Process:
	% Initialize the weight distribution
	For
	For % Train a base learner, from using distribution
	% Measure the error of
	% Determine the weight of
	% Update the distribution, where is a normalized factor with enables to be a distribution
	end.
	Output: