Combining multiple classifiers via combining schemes or meta-learners has led to substantial improvements in many classification problems. One of the challenging tasks is to choos...
Traditional approaches to combining classifiers attempt to improve classification accuracy at the cost of increased processing. They may be viewed as providing an accuracy-speed tr...
Kumar Chellapilla, Michael Shilman, Patrice Simard
Using Boolean AND and OR functions to combine the responses of multiple one- or two-class classifiers in the ROC space may significantly improve performance of a detection system o...
With rejection strategies in a handwriting recognition system, we are able to improve the reliability and accuracy of the recognized characters. In this paper, we propose several ...
Xu-Cheng Yin, Hong-Wei Hao, Yun-Feng Tang, Jun Sun...
Combining multiple classifiers is of particular interest in multimedia applications. Each modality in multimedia data can be analyzed individually, and combining multiple pieces of...
Machine learning is an increasingly used computational tool within human-computer interaction research. While most researchers currently utilize an iterative approach to refining ...