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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/142350

Title:	Network based discriminant analysis for multiclassification
Authors:	陳立榜 Chen, Li-Pang
Contributors:	統計系
Date:	2021-12
Issue Date:	2022-10-07 13:43:11 (UTC+8)
Abstract:	With the rapid advance of information technology, complex data are collected easily, and undoubtedly, they become more challenging than we expect. In addition, network structure is important feature and is ubiquitous in high-dimensional data because of strong or weak correlations among variables. Our main interest is to use predictors to do multiclassification. While discriminant analysis is one of supervised learning methods to deal with multiclassification and relevant extensions have been explored, little method has been available to deal with multiclassification with network structures accommodated. To incorporate the network structure and improve the accuracy of classification, we propose network based linear discriminant analysis and quadratic discriminant analysis in this paper. The main advantage of the proposed methods is to incorporate network structure of predictors and analyze the classification with multiclass responses instead of restricting on binary responses. In addition, the proposed methods are easy to compute and implement. Finally, numerical studies are conducted to assess the performance of the proposed methods, and numerical results verify that the proposed methods outperform their competitors.
Relation:	2021年統計學術研討會暨台、日、韓國際統計學術研討會, 輔仁大學統計資訊學系、中國統計學社
Data Type:	conference
Appears in Collections:	[統計學系] 會議論文

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