Resampling Methods and Machine Learning
Liang Hong · Chinese Journal of Computers · 2009
In Boosting algorithm complex natural model is approximated by the linear combination of weak learners.Due to its excellent interpretability and prediction power,Boosting has become an intensive focus in computer science field.However,it is only considered as an optimizing procedure with a specific loss function,whose nature in statistics has never obtained sufficient attention.In essence,a statistical perspective of Boosting algorithm is brought out in this paper,i.e.,an interesting special case of resampling methods.The authors hope the current situation of excessive attention being paid to the performance of algorithm while the characteristic of data being ignored will be changed,such that the tasks of high dimensional and large volume data generated in an uncontrolled manner could be tackled more appropriately.