Package: RMKL
Type: Package
Title: Multiple Kernel Learning for Classification or Regression
        Problems
Version: 1.0
Date: 2019-04-11
Author: Christopher Wilson, 
 Kaiqiao Li
Maintainer: Christopher Wilson <cwilso6@clemson.edu>
Description: Provides R and C++ function that enable the user to conduct multiple 
 kernel learning (MKL) and cross validation for support vector machine (SVM) models. 
 Cross validation can be used to identify kernel shapes and hyperparameter 
 combinations that can be used as candidate kernels for MKL. There are three 
 implementations provided in this package, namely SimpleMKL Alain Rakotomamonjy et. al
 (2008), Simple and Efficient MKL Xu et. al (2010), and Dual augmented Lagrangian MKL
 Suzuki and Tomioka (2011) <doi:10.1007/s10994-011-5252-9>. These methods identify the convex combination of 
 candidate kernels to construct an optimal hyperplane.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), caret, kernlab, stats, e1071
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
LazyLoad: yes
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-24 14:53:19 UTC; 4468179
Repository: CRAN
Date/Publication: 2019-04-25 15:20:03 UTC
Built: R 4.0.2; x86_64-w64-mingw32; 2020-08-02 16:23:33 UTC; windows
Archs: i386, x64
