期刊論文

學年 103
學期 1
出版(發表)日期 2014-11-01
作品名稱 Exploratory data analysis of interval-valued symbolic data with matrix visualization
作品名稱(其他語言)
著者 Kao, Chiun-How; Nakano, Junji; Shieh, Sheau-Hue; Tien, Yin-Jing; Wu, Han-Ming; Yang, Chuan-kai; Chen, Chun-houh
單位 淡江大學數學學系
出版者 Amsterdam: Elsevier BV
著錄名稱、卷期、頁數 Computational Statistics & Data Analysis 79, pp.14-29
摘要 Symbolic data analysis (SDA) has gained popularity over the past few years because of its potential for handling data having a dependent and hierarchical nature. Amongst many methods for analyzing symbolic data, exploratory data analysis (EDA: Tukey, 1977) with graphical presentation is an important one. Recent developments of graphical and visualization tools for SDA include zoom star, closed shapes, and parallel-coordinate-plots. Other studies project high dimensional symbolic data into lower dimensional spaces using symbolic data versions of principal component analysis, multidimensional scaling, and self-organizing maps. Most graphical and visualization approaches for exploring symbolic data structure inherit the advantages of their counterparts for conventional (non-symbolic) data, but also their disadvantages. Here we introduce matrix visualization (MV) for visualizing and clustering symbolic data using interval-valued symbolic data as an example; it is by far the most popular symbolic data type in the literature and the most commonly encountered one in practice. Many MV techniques for visualizing and clustering conventional data are converted to symbolic data, and several techniques are newly developed for symbolic data. Various examples of data with simple to complex structures are brought in to illustrate the proposed methods.
關鍵字 Symbolic data analysis; Interval-valued data; Matrix visualization; Generalized association plots; Proximity matrix; Exploratory data analysis; EDA
語言 en
ISSN 0167-9473 1872-7352
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Chen, Chun-houh
審稿制度
國別 NLD
公開徵稿
出版型式 ,電子版,紙本
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