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NetDA: An R Package for Network-Based Discriminant Analysis Subject to Multilabel Classes

In this paper, we introduce the R package NetDA, which aims to deal with multiclassification with network structures in predictors accommodated. To address the natural feature of network structures, we apply Gaussian graphical models to characterize dependence structures of the predictors and direct...

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Bibliographic Details
Published in:Journal of probability and statistics 2022-09, Vol.2022, p.1-14
Main Author: Chen, Li-Pang
Format: Article
Language:English
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Summary:In this paper, we introduce the R package NetDA, which aims to deal with multiclassification with network structures in predictors accommodated. To address the natural feature of network structures, we apply Gaussian graphical models to characterize dependence structures of the predictors and directly estimate the precision matrix. After that, the estimated precision matrix is employed to linear discriminant functions and quadratic discriminant functions. The R package NetDA is now available on CRAN, and the demonstration of functions is summarized as a vignette in the online documentation.
ISSN:1687-952X
1687-9538
DOI:10.1155/2022/1041752