时变微阵列数据集:共表达检测

S. Minz, I. K. A. Abughali
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引用次数: 1

摘要

本文确定了VCD算法[1]的改进范围。本文提出的改进考虑消除参数λ和zp的用户输入。根据两个实验的结果,对基本算法和所提算法进行了实现和比较。对传统的廓形系数作为评价参数进行了改进。两种算法的结果通过独立t检验进行比较。虽然在实验-1中基本算法与提出算法的性能没有明显差异,但用户不需要对增强算法进行参数设置。由于大多数聚类算法对数据输入的顺序很敏感,实验2的结果表明,本文算法的结果不受数据输入顺序的影响。此外,本文提出的算法以分层的方式产生聚类结果。
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Time-varying microarray data sets: Co-expression detection
The scope for improvements in the VCD algorithm [1] has been identified in this paper. The enhancement proposed in this paper considers to eliminate the user inputs for the parameters λ and zp. The base algorithm and the proposed algorithm have been implemented and compared based on the outcomes of the two experiments. The traditional Silhouette coefficient has also been modified as an evaluation parameter. Results of both algorithms are compared by independent t-test. Although no significant difference has been observed in the performances of the base algorithm and the proposed algorithm in the experiment-1, the user need not do parameter setting for the enhanced algorithm. As most clustering algorithms are sensitive to the order of the data input, the results of experiment-2 show that the outcome of the proposed algorithm is not affected by the order of data input. More over the proposed algorithm yields cluster outcomes in hierarchical manner.
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