聚类分析
追踪
口译(哲学)
散点图
计算机科学
绘图(图形)
多元统计
数据挖掘
算法
生物系统
模式识别(心理学)
人工智能
数学
统计
机器学习
生物
操作系统
程序设计语言
作者
M. Daszykowski,Beata Walczak,D.L. Massart
出处
期刊:Journal of Chemical Information and Computer Sciences
[American Chemical Society]
日期:2002-05-01
卷期号:42 (3): 500-507
被引量:92
摘要
The main principles and the algorithm of a density-based clustering approach, OPTICS, are described, and its unique properties, such as the ability to reveal clusters of arbitrary shapes and different densities, are illustrated on simulated and real spectral and chromatographic data sets. A "reachability plot" visualizing density fluctuations of data in multivariate space and a "color map" relating the original and/or descriptive features with data clustering allow a deeper insight into the data structure and its interpretation in chemical terms.
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