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 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.

Abstract licence: CC BY-NC-ND

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