Atanassov直觉模糊集的三项属性描述作为属性选择的基础

E. Szmidt, J. Kacprzyk, Paweł Bujnowski
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引用次数: 6

摘要

本文提出了一种在直觉模糊集模型中进行属性选择的新方法。我们进一步发展了我们之前的论文,其中该方法已经扩展,并进行了第一次计算测试,即,该方法与主成分分析(PCA)进行了比较。在这里,我们测试该方法在使用增益比时与选择相比如何表现。我们考虑分类问题,并尝试减少属性的数量,以避免获得更差的结果。
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Three term attribute description of Atanassov's Intuitionistic Fuzzy Sets as a basis of attribute selection
We propose here a new proposal for attribute selection in the models expressed by the intuitionistic fuzzy sets. We further develop our previous paper in which the approach was already extended and the first computational tests were performed, i.e., the method was compared with the Principal Component Analysis (PCA). Here we test how the method behaves in comparison with the selection while using the Gain Ratio. We consider classification problems and try to reduce the number of attributes to not obtain substantially worse results.
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