Bayes classifier and loss functions

E. Ocelíková, D. Klimesová
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Abstract

This paper deals with the classification of objects into the limited number of classes. The objects are characterized by n-features. The paper focuses on the Bayes classifier based on the probability principle with the fixed number of the features during the classification process. The Bayes classifier which uses criterion of the minimum error was applied on the set of the multispectral data. They represent real images of the Earth surface obtained from remote Earth sensing. The paper describes experience and results obtained during the classification of extensive set of these multispectral data with the Bayes classifier using the symmetric and diagonal loss function.
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贝叶斯分类器和损失函数
本文研究的是在有限的类别中对对象进行分类的问题。对象有n个特征。本文重点研究了基于概率原理的贝叶斯分类器,分类过程中特征个数固定。采用误差最小准则的贝叶斯分类器对多光谱数据集进行分类。它们代表了从遥感获得的地球表面的真实图像。本文介绍了贝叶斯分类器利用对称和对角损失函数对这些多光谱数据的广泛集进行分类的经验和结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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