Package: SRCS 1.1

Pablo J. Villacorta

SRCS: Statistical Ranking Color Scheme for Multiple Pairwise Comparisons

Implementation of the SRCS method for a color-based visualization of the results of multiple pairwise tests on a large number of problem configurations, proposed in: I.G. del Amo, D.A. Pelta. SRCS: a technique for comparing multiple algorithms under several factors in dynamic optimization problems. In: E. Alba, A. Nakib, P. Siarry (Eds.), Metaheuristics for Dynamic Optimization. Series: Studies in Computational Intelligence 433, Springer, Berlin/Heidelberg, 2012.

Authors:Pablo J. Villacorta <[email protected]>

SRCS_1.1.tar.gz
SRCS_1.1.tar.gz(r-4.5-noble)SRCS_1.1.tar.gz(r-4.4-noble)
SRCS_1.1.tgz(r-4.4-emscripten)SRCS_1.1.tgz(r-4.3-emscripten)
SRCS.pdf |SRCS.html✨
SRCS/json (API)

# Install 'SRCS' in R:
install.packages('SRCS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • ML1 - Performance of 6 different supervised classification algorithms on eight noisy datasets
  • MPB - Performance of 8 different dynamic optimization algorithms on the Moving Peaks Benchmark
  • MPBall - Performance of 3 different dynamic optimization algorithms on the Moving Peaks Benchmark captured at five time moments of the execution

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4 exports 0.00 score 0 dependencies 34 scripts 147 downloads

Last updated 9 years agofrom:888f60a186. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-linuxNOTEAug 22 2024

Exports:animatedplotsingleplotSRCScomparisonSRCSranks

Dependencies:

SRCS: Statistical Ranking Color Scheme for Multiple Pairwise Comparisons

Rendered fromSRCS.pdf.asisusingR.rsp::asison Aug 22 2024.

Last update: 2015-06-30
Started: 2015-06-30