利用伽罗瓦格挖掘复杂的水生生物数据

Aurélie Bertaux, Agnès Braud, F. Ber
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引用次数: 5

摘要

我们已经使用伽罗瓦格来挖掘水生生物数据。这些数据是关于大型植物的,它们是生活在水体中的宏观植物。这些植物具有几种生物特性,具有几种形态。我们的目的是根据植物的共同性状和形态进行聚类,并找出性状之间的关系。伽罗瓦格是实现这一目标的有效方法,但适用于二进制数据。在本文中,我们详细介绍了将复杂的水生生物数据转换为二进制数据的几种方法,并比较了利用伽罗瓦格获得的第一个结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mining Complex Hydrobiological Data with Galois Lattices
We have used Galois lattices for mining hydrobiological data. These data are about macrophytes, that are macroscopic plants living in water bodies. These plants are characterized by several biological traits, that own several modalities. Our aim is to cluster the plants according to their common traits and modalities and to find out the relations between traits. Galois lattices are efficient methods for such an aim, but apply on binary data. In this article, we detail a few approaches we used to transform complex hydrobiological data into binary data and compare the first results obtained thanks to Galois lattices.
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