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Research on the application of pattern selection algorithm in bioinformatic data bases on mutual information

机译:模式选择算法在互信息上生物信息学数据库中的应用研究

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Pattern selection is an important part in the research fields of data mining and pattern recognition, especially for the high-dimensional data in the Bioinformatics. In this paper, a new pattern selection algorithm was proposed to finish pattern selection bases on Mutual Information. Pattern subset evaluation index was researched to ensure the best feature subset was selected. The algorithm bases on the correlation of patterns and label, as well as the redundancy between the patterns. Fuzzy Pattern Subset Evaluation Index was researched to make sure which is the best subset for the pattern subset evaluation. To verify the effectiveness of the method, some experiments were finished with the data of gene expression data (Leiden University) and UCI datasets. The experimental results indicate that the algorithm achieved better results.
机译:图案选择是数据挖掘和模式识别研究领域的重要组成部分,特别是对于生物信息学中的高维数据。本文提出了一种新的模式选择算法来完成相互信息的模式选择基础。研究了模式子集评估索引以确保选择了最佳功能子集。该算法基于模式和标签的相关性,以及模式之间的冗余。研究了模糊模式子集评估指标以确保这是模式子集评估的最佳子集。为了验证该方法的有效性,使用基因表达数据(Leiden University)和UCI数据集的数据进行了一些实验。实验结果表明该算法取得了更好的结果。

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