<abstract xmlns="http://www.w3.org/1999/xhtml"><p>To have simple and efficient confidence machine learning is an important focus in confidence machine researches. Using one class classifier as a tool, the paper applies it twice for two-class classification problems. Setting reject options and a multi-layer ensemble learning method are used in this study. In this method there is no necessity to set up a specific threshold and the confidence computation is omitted. Realizing five experiments, the study proves it as efficient.</p></abstract>

To have simple and efficient confidence machine learning is an important focus in confidence machine researches. Using one class classifier as a tool, the paper applies it twice for two-class classification problems. Setting reject options and a multi-layer ensemble learning method are used in this study. In this method there is no necessity to set up a specific threshold and the confidence computation is omitted. Realizing five experiments, the study proves it as efficient.

Research Of Two Class Confidence Classification Based On One Class Classifier

School of Computer and Information Technology, Beijing Jiao Tong University, Beijing 100044, China

Shen Zhen Institute of Information Technology, Shen Zhen, Guang Dong 518172, China

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Research Of Two Class Confidence Classification Based On One Class Classifier"}

To have simple and efficient confidence machine learning is an important focus in confidence machine researches. Using one class classifier as a tool, the...

Research Of Two Class Confidence Classification Based On One Class Classifier

Online veröffentlicht: 30. Dez. 2014

Seitenbereich: 28 - 39

DOI: https://doi.org/10.2478/cait-2014-0041

© by Jiang Fangchun

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.