@inproceedings{1e61ba3e236a4b158975953873be4917,
title = "A feature selection based on minimum upper bound of bayes error",
abstract = "This paper1 presents a novel feature selection scheme based on the upper bound of Bayes error under normal distribution for the multi-class dimension reduction problem. The upper bound of Bayes error in the multi-class problem is represented by the sum of the upper bound of Bayes error of every two-class pair. In order to obtain an accurate solution of the feature selection transform matrix in term of the minimum upper bound of Bayes error, a recursive algorithm based on gradient method is developed. The principal component analysis (PCA) is used as a pre-processing to reduce the intractably heavy computation burden of the recursive algorithm. The superior experimental results on the handwritten digit recognition with the MNIST database demonstrate the effectiveness of our proposed method.",
keywords = "Fast feature selection based on minimum error bound (FFME), Feature selection based on minimum error bound (FME), Handwritten digit recognition, PCA pre-processing, Recursive algorithm",
author = "Guorong Xuan and Zhenping Zhang and Peiqi Chai and Shi, {Yun Q.} and Dongdong Fu",
year = "2005",
month = jan,
day = "1",
doi = "10.1109/MMSP.2005.248662",
language = "English (US)",
isbn = "0780392892",
series = "2005 IEEE 7th Workshop on Multimedia Signal Processing",
publisher = "IEEE Computer Society",
booktitle = "2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005",
address = "United States",
note = "2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005 ; Conference date: 30-10-2005 Through 02-11-2005",
}