首页> 美国卫生研究院文献>BMC Bioinformatics >A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data analysis
【2h】

A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data analysis

机译:一种评估距离函数的内在判别能力及其与聚类算法相互作用以进行微阵列数据分析的方法

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

BackgroundClustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research.
机译:背景技术聚类是科学研究中最著名的活动之一,也是从统计学到计算机科学等许多学科研究的对象。按照Handl等人的观点,可以概括为三个步骤:(1)选择距离函数; (2)选择聚类算法; (3)选择一种验证方法。尽管在许多科学领域几乎看不到这种纯粹的聚类方法,但是如果从聚类分析得出的结论必须与生物医学研究相关,则基因组数据需要引起人们的关注。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号