rcccd: Class Cover Catch Digraph Classification

Fit Class Cover Catch Digraph Classification models that can be used in machine learning. Pure and proper and random walk approaches are available. Methods are explained in Priebe et al. (2001) <doi:10.1016/S0167-7152(01)00129-8>, Priebe et al. (2003) <doi:10.1007/s00357-003-0003-7>, and Manukyan and Ceyhan (2016) <doi:10.48550/arXiv.1904.04564>.

Version: 0.3.2
Depends: R (≥ 4.2)
Imports: Rcpp, RANN, Rfast, proxy
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-04-24
Author: Fatih Saglam ORCID iD [aut, cre]
Maintainer: Fatih Saglam <saglamf89 at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
CRAN checks: rcccd results


Reference manual: rcccd.pdf


Package source: rcccd_0.3.2.tar.gz
Windows binaries: r-devel: rcccd_0.3.2.zip, r-release: rcccd_0.3.2.zip, r-oldrel: rcccd_0.3.2.zip
macOS binaries: r-release (arm64): rcccd_0.3.2.tgz, r-oldrel (arm64): not available, r-release (x86_64): rcccd_0.3.2.tgz, r-oldrel (x86_64): not available

Reverse dependencies:

Reverse depends: imbalanceDatRel


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