TangentBoost is a robust boosting algorithm. The method combines loss function and weak classi…ers. In addition, TangentBoost gives penalties not only misclassi…cation but also true classi…cation margin in order toget more stable classi…ers. Despite the fact that the method is good one inob ject tracking, propensity scores are obtained improperly in the algorithm.The problem causes mislabeling of observations in the statistical classi…cation.In this paper, there is a correction proposal for TangentBoost algorithm. Afterthe correction on the algorithm, there is a simulation study for the new algorithm. The results show that correction on the algorithm is useful for binaryclassi…cation
Other ID | JA94FS58MR |
---|---|
Journal Section | Research Article |
Authors | |
Publication Date | August 1, 2018 |
Submission Date | August 1, 2018 |
Published in Issue | Year 2018 Volume: 67 Issue: 2 |
Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics.
This work is licensed under a Creative Commons Attribution 4.0 International License.