Cognitively inspired classification for adapting to data distribution changes

• Main Authors: Sit, Wing Yee, Mao, K. Z.
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2013
• 主題: DRNTU::Engineering::Electrical and electronic engineering
• 在線閱讀: https://hdl.handle.net/10356/96469; http://hdl.handle.net/10220/11982

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...