DWDLarge version 0 -- a MATLAB and R software for large scale distance weighted discrimination

Authors: Xin-Yee Lam, J. S. Marron, Defeng Sun, and Kim-Chuan Toh

This software package is for solving the distance weighted discrimination problem of the following form:

where is the sample size, is the feature dimension, and is the penalty parameter. Here, the input is a matrix whose columns are the feature vectors, and is a vector containing binary classification label . The notation is defined to be . The exponent is typically set to or . The main algorithm for solving is a symmetric Gauss-Seidel based ADMM method. It will output the result for which is a hyperplane separating the two classes of data and is a slack variable to allow the possibility that the positive and negative data points may not be separated cleanly by the hyperplane.

For more details, please see the 'README' file in the package.

Important note:


Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018), Fast algorithms for large scale generalized distance weighted discrimination, Journal of Computational and Graphical Statistics, forthcoming. https://arxiv.org/abs/1604.05473

Copyright: This version of DWDLarge is distributed under the GNU General Public License 2.0. For commercial applications that may be incompatible with this license, please contact the authors to discuss alternatives.


You can download the MATLAB package here: DWDLarge.zip

You can download the R package here: https://cran.r-project.org/web/packages/DWDLargeR/index.html

User's guide is included in the package. Below are some basic setup guide: