Visualizing Class Specific Heterogeneous Tendencies in Categorical Data
Visualizing Class Specific Heterogeneous Tendencies in Categorical Data
复制标题
可视化分类数据中特定类别的异质趋势
DOI:
10.1080/10618600.2022.2035737
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发表时间:
2022
影响因子:
2.4
通讯作者:
Velden Michel van de
中科院分区:
文献类型:
--
作者:
Takagishi Mariko;Velden Michel van de
In multiple correspondence analysis, both individuals (observations) and categories can be represented in a biplot that jointly depicts the relationships across categories and individuals, as well as the associations between them. Additional information about the individuals can enhance interpretation capacities, such as by including class information for which the interdependencies are not of immediate concern, but that facilitate the interpretation of the plot with respect to relationships between individuals and categories. This article proposes a new method which we call multiple-class cluster correspondence analysis that identifies clusters specific to classes. The proposed method can construct a biplot that depicts heterogeneous tendencies of individual members, as well as their relationships with the original categorical variables. A simulation study to investigate the performance of the proposed method and an application to data regarding road accidents in the United Kingdom confirms the viability of this approach. Supplementary materials for this article are available online.
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影响因子:
3.8
作者:
S. Buuren;J. Leeuw
通讯作者:
J. Leeuw
DOI:
10.1198/jcgs.2010.07134
发表时间:
2010
期刊:
影响因子:
--
作者:
J. Gower;P. Groenen;M. van de Velden
通讯作者:
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影响因子:
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作者:
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F. Palumbo
DOI:
10.1007/bf02294498
发表时间:
1991
期刊:
影响因子:
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作者:
Y. Takane;H. Yanai;S. Mayekawa
通讯作者:
S. Mayekawa
影响因子:
3
作者:
BOCKENHOLT, U;BOCKENHOLT, I
通讯作者:
BOCKENHOLT, I