基于标记信息的遗传规划方法获取带有通配符的保块外平面图模式

2019 IEEE 11th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2019-11-01 DOI:10.1109/IWCIA47330.2019.8955031

Fumiya Tokuhara, Shiho Okinaga, T. Miyahara, Yusuke Suzuki, T. Kuboyama, Tomoyuki Uchida

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引用次数: 1

摘要

机器学习和从图结构数据中挖掘数据已经受到了广泛的关注。许多化合物可以用外平面图表示。提出了一种利用正例的标签连接信息，利用遗传规划方法，从正例和负例外平面图数据中获取保留特征块的外平面图模式，并为顶点和边标记添加通配符。我们报告了真实化合物数据和合成数据的实验结果。

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Using Label Information in a Genetic Programming Based Method for Acquiring Block Preserving Outerplanar Graph Patterns with Wildcards

Machine learning and data mining from graph structured data have gained much attention. Many chemical compounds can be expressed by outerplanar graphs. We propose a method for acquiring characteristic block preserving outerplanar graph patterns with wildcards for vertex and edge labels, from positive and negative outerplanar graph data, by Genetic Programming using label connecting information of positive examples. We report experimental results on real chemical compound data and synthetic data.

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来源期刊

2019 IEEE 11th International Workshop on Computational Intelligence and Applications (IWCIA)

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