Enables researchers to visualize the prediction performance of any algorithm on the individual level (or close to it), given that the predicted outcome is either binary or continuous. Visual results are instantly comprehensible.
| Version: | 0.1 |
| Depends: | R (≥ 3.3.0) |
| Imports: | Rdpack, ggplot2, reshape2 |
| Suggests: | knitr, rmarkdown |
| Published: | 2022-05-24 |
| DOI: | 10.32614/CRAN.package.predictMe |
| Author: | Marcel Miché |
| Maintainer: | Marcel Miché <marcel.miche.predictme at gmail.com> |
| License: | MIT + file LICENSE |
| URL: | https://github.com/mmiche/predictMe |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | predictMe results |
| Reference manual: | predictMe.html , predictMe.pdf |
| Vignettes: |
predictMe: Why and how to? (source, R code) |
| Package source: | predictMe_0.1.tar.gz |
| Windows binaries: | r-devel: predictMe_0.1.zip, r-release: predictMe_0.1.zip, r-oldrel: predictMe_0.1.zip |
| macOS binaries: | r-release (arm64): predictMe_0.1.tgz, r-oldrel (arm64): predictMe_0.1.tgz, r-release (x86_64): predictMe_0.1.tgz, r-oldrel (x86_64): predictMe_0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=predictMe to link to this page.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.