AdBagging:adaptive sampling parameters online bagging algorithm
Shiyin Li · Jisuanji gongcheng yu sheji · 2011
By analyzing the concept drift problem in data stream classification,a new algorithm based on online bagging algorithm named adaptive lambda bagging algorithm(AdBagging) is introduced.The new algorithm dynamically adjusts the sampling parameters of Poisson distribution in online bagging algorithm based on the number of misclassified samples in data stream classification.Through this procedure the new algorithm could give more attention to the misclassified samples and give little attention to the right classified samples.At the same time the learning weight of samples for algorithm can be adjusted according to the temporal order.So the algorithm could solve the concept drift problem in data stream classification.Experiments on synthesize and real data sets prove that the algorithm is effective.