用有限的特征空间进行分类:通过拒绝错误分类来提高质量

2014 4th World Congress on Information and Communication Technologies (WICT 2014) Pub Date : 2014-12-01 DOI:10.1109/WICT.2014.7077322

W. Homenda, A. Jastrzębska, W. Pedrycz, Radosław Piliszek

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引用次数: 1

摘要

分类，特别是在特征空间很小的情况下，容易出现错误。当从样本中获取数据以计算期货价值的成本很高时，这一点更为重要。我们研究了限制特征空间对构建的分类器性能的影响，以及如何通过拒绝错误分类的元素来提高分类质量。

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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Classification with a limited space of features: Improving quality by rejecting misclassifications

Classification, especially in the case of a small space of features, is prone to errors. This is more important when it is costly to gain data from samples to calculate the values for futures. We study what effect limiting the space of features has on the performance of built classifiers and how the quality of classification can be improved by rejecting misclassified elements.

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2014 4th World Congress on Information and Communication Technologies (WICT 2014)

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