古德曼-克鲁斯卡尔系数及其在癌症基因诊断中的应用。

The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer.

作者信息

Jaroszewicz Szymon, Simovici Dan A, Kuo Winston P, Ohno-Machado Lucila

机构信息

Department of Computer Science, University of Massachusetts, Boston, MA 02125, USA.

出版信息

IEEE Trans Biomed Eng. 2004 Jul;51(7):1095-102. doi: 10.1109/TBME.2004.827267.

DOI:10.1109/TBME.2004.827267

PMID:15248526

Abstract

Increasing interest in new pattern recognition methods has been motivated by bioinformatics research. The analysis of gene expression data originated from microarrays constitutes an important application area for classification algorithms and illustrates the need for identifying important predictors. We show that the Goodman-Kruskal coefficient can be used for constructing minimal classifiers for tabular data, and we give an algorithm that can construct such classifiers.

摘要

生物信息学研究激发了人们对新模式识别方法日益增长的兴趣。源自微阵列的基因表达数据分析构成了分类算法的一个重要应用领域，并说明了识别重要预测因子的必要性。我们表明古德曼-克鲁斯卡尔系数可用于构建表格数据的最小分类器，并给出了一种能够构建此类分类器的算法。