PLFD

PLFD-package

The portmanteau local feature discriminant approach first identifies the local discriminant features and their differential structures, then constructs the discriminant rule by pooling the identified local features together. This method is applicable to high-dimensional matrix-variate data. See the paper by Xu, Luo and Chen (2021, tools:::Rd_expr_doi("10.1007/s13171-021-00255-2")).

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The portmanteau local feature discriminant approach first identifies the local
discriminant features and their differential structures, then constructs the
discriminant rule by pooling the identified local features together. This method
is applicable to high-dimensional matrix-variate data.
See the paper by Xu, Luo and Chen (2021, <doi:10.1007/s13171-021-00255-2>).

Zengchao Xu

Portmanteau Local Feature Discrimination for Matrix-Variate Data

Shan Luo

Zehua Chen

PLFD-package function

Maintainer: Zengchao Xu <a href="/link/zengc.xu%40aliyun.com?package=PLFD&version=0.2.0" data-mini-rdoc="PLFD::zengc.xu@aliyun.com">zengc.xu@aliyun.com</a>
Authors:<ul>
<li>Shan Luo</li>
<li>Zehua Chen</li>
</ul>

Author

PLFD: Portmanteau Local Feature Discrimination for Matrix-Variate Data — PLFD-package

Maintainer: Zengchao Xu <a href='mailto:zengc.xu@aliyun.com'>zengc.xu@aliyun.com</a>
Authors:<ul>
<li>Shan Luo</li>
<li>Zehua Chen</li>
</ul>

PLFD-package: PLFD: Portmanteau Local Feature Discrimination for Matrix-Variate Data

Description

Arguments

Author

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