@inproceedings{c4326e1117ed4fd2b21eb90f63573c5e,
title = "A simple implementation of the stochastic discrimination for pattern recognition",
abstract = "The method of stochastic discrimination (SD) introduced by Kleinberg ([6,7])is a new method in pattern recognition. It works by producing weak classifiers and then combining them via the Central Limit Theorem to form a strong classifier. SD is overtraining-resistant, has a high convergence rate, and can work quite well in practice. However, some strict assumptions involved in SD and the difficulties in understanding SD have limited its practical use. In this paper, we present a simple algorithm of SD for two-class pattern recognition. We illustrate the algorithm by applications in classifying the feature vectors from some real and simulated data sets. The experimental results show that SD is fast, effective, and applicable.",
author = "Dechang Chen and Xiuzhen Cheng",
year = "2000",
doi = "10.1007/3-540-44522-6_91",
language = "English",
isbn = "3540679464",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "882--887",
editor = "Ferri, {Francesc J.} and Inesta, {Jose M.} and Adnan Amin and Pavel Pudil",
booktitle = "Advances in Pattern Recognition - Joint IAPR International Workshops, SSPR 2000 and SPR 2000, Proceedings",
note = "8th Meeting of the International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2000 and 3rd International Workshop on Statistical Techniques in Pattern Recognition, SPR 2000 ; Conference date: 30-08-2000 Through 01-09-2000",
}