A Comparison on Random Forest and Bagging Classification Tree in Classification
Xie Bang-chang · Tongji yu xinxi luntan · 2010
The purpose of this paper is to explain why random forest is more competitive than Bagging classification tree in classification from two theoretical views by experiment data.Our analysis in two theoretical views may dissipate misunderstandings existing in the two ensemble methods,and the second analysis suggested by us shows random forest is more successful than bagging in bias reduction and may more evidently explain the reason that random forest is prior to Bagging classification tree than the first one.