PLFD
Portmanteau Local Feature Discrimination for Matrix-Variate Data
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).
- Version0.2.0
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?Yes
- Languageen-US
- Last release01/10/2023
Documentation
Team
Zengchao Xu
Shan Luo
Show author detailsRolesAuthorZehua Chen
Show author detailsRolesAuthor
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Last 30 days
This package has been downloaded 142 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,974 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 27 downloads.
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Dependencies
- Imports2 packages
- Suggests3 packages
- Linking To2 packages