Classification Algorithm of Kernel-based in Adaboost
Tao Li · Computer Knowledge and Technology · 2011
Boosting is a new method of ensemble machine learning developed from the theory of Statistical Learning Theory(STL),and it has a great application on the pattern classification field.The theory of Boosting and the classical algorithm of AdaBoost are studied at first,then it is introduced three kinds of kernel function(Polynomial kernel,Radial Basis Function,Sigmoid kernel function) integrated weak classifier for AdaBoost.Then it applied to two conclusions about cancer data set by experimental verification of a nuclear function as a weak classifier integrates the good performance of AdaBoost classifiers.