Perform Linear Classification with Multi-way Data

Overview

MultiwayClassification

This is an R package to perform linear classification for data with multi-way structure. The distance-weighted discrimination (DWD) or support vector machine (SVM) classification objectives are optimized under the assumption that the multi-way coefficients have low rank [1]. Additional functions perform multiway DWD with sparsity [2]. This package depends on the packages DWD (for DWD), kernlab (for SVM), and sdwd (for sparse DWD). DWD is not currently available on CRAN, and so will need to be installed via its url:

install.packages("https://cran.r-project.org/src/contrib/Archive/DWD/DWD_0.11.tar.gz",repos = NULL, type = "source")

The MultiwayClassification package can then be installed, directly from GitHub, using the devtools library:

install.packages('devtools')
library(devtools)
install_github("lockEF/MultiwayClassification")

Code for this package was written primarily by Tianmeng Lyu (for multiway DWD and SVM) and Bin Guo (for multiway sparse DWD).

[1] Lyu, T., Lock, E.F., & Eberly, L. E. (2017). Discriminating sample groups with multi-way data. Biostatistics, 18 (3): 434–450. https://arxiv.org/abs/1606.08046 .

[2] Guo, B., Eberly, L.E., Henry, P.G., Lenglet, C. & Lock, E. F. (2020). Sparse multiway distance weighted discrimination. Preprint.

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