A CORRECTION ON TANGENTBOOST ALGORITHM

Abstract

TangentBoost is a robust boosting algorithm. The method com-bines loss function and weak classifers. In addition, TangentBoost gives penal-ties not only misclassifcation but also true classifcation margin in order toget more stable classifers. Despite the fact that the method is good one inobject tracking, propensity scores are obtained improperly in the algorithm.The problem causes mislabeling of observations in the statistical classifcation.In this paper, there is a correction proposal for TangentBoost algorithm. Afterthe correction on the algorithm, there is a simulation study for the new algo-rithm. The results show that correction on the algorithm is useful for binaryclassifcation.