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摘要

在过去,我们已经开发并提出了模糊决策树,最近又提出了一个扩展,称为模糊决策森林。森林背后的思想不仅是表示多棵树,而且表示每棵树的所有级别的测试选择。得到的树实际上是一个三维树。一个二维切片相当于一个决策树。森林允许在决策树的部分或全部节点中进行多个测试选择。这些替代测试可以用来提高树的分类精度。然而,拥有多个测试选择的主要优点是,当测试数据中的特征不可靠或只是缺少时,可以有可选的测试决策。在本文中,我们概述了模糊决策森林背后的思想,并通过一些缺失特征的实验来说明其增强的功能。
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Fuzzy Decision Forest
In the past, we have developed and presented a Fuzzy Decision Tree, more recently followed by an extension called a Fuzzy Decision Forest. The idea behind the forest is not only to represent multiple trees, but also to represent test alternatives at all levels of every tree. The resulting tree is in fact a 3-dimensional tree. A two-dimensional slice is equivalent to a single decision tree. The forest allows multiple choices of tests in some or all nodes of the decision tree. These alternative tests can be used to enhance the classification accuracy of the tree. However, the major advantage of having multiple test choices is to have alternative test decisions when features in test data are unreliable or just missing. In the paper, we overview the ideas behind Fuzzy Decision Forest, and we illustrate its enhanced capabilities with a number of experiments with missing features.
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