Cognitively inspired classification for adapting to data distribution changes

• المؤلفون الرئيسيون: Sit, Wing Yee, Mao, K. Z.
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2013
• الموضوعات: DRNTU::Engineering::Electrical and electronic engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/96469; http://hdl.handle.net/10220/11982
• المؤسسة: Nanyang Technological University

In pattern classification, the test data is expected to lie in the domain covered by the training data. But in practical scenarios, this may not necessarily be true. To improve the adaptability, the classifier should be able to generalize well even when there are changes in the input distribution. T...