Package: predictMe 0.2

predictMe: Visualize Individual Prediction Performance

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.

Authors:Marcel Miché

predictMe_0.2.tar.gz
predictMe_0.2.zip(r-4.7)predictMe_0.2.zip(r-4.6)predictMe_0.2.zip(r-4.5)
predictMe_0.2.tgz(r-4.6-any)predictMe_0.2.tgz(r-4.5-any)
predictMe_0.2.tar.gz(r-4.7-any)predictMe_0.2.tar.gz(r-4.6-any)
predictMe_0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
predictMe/json (API)

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

Bug tracker:https://github.com/mmiche/predictme/issues

On CRAN:

Conda:

3.70 score 1 stars 3 scripts 141 downloads 8 exports 25 dependencies

Last updated from:2733987ac5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK138
source / vignettesOK145
linux-release-x86_64OK146
macos-release-arm64OK160
macos-oldrel-arm64OK165
windows-develOK84
windows-releaseOK76
windows-oldrelOK83
wasm-releaseOK107

Exports:addContinuousbinBinarybinContinuousget2by2makeDiffPlotmakeDiffPlotColormakeTablePlotquickSim

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclemagrittrplyrR6rbibutilsRColorBrewerRcppRdpackreshape2rlangS7scalesstringistringrvctrsviridisLitewithr

predictMe: Why and how to?

Marcel Miché

Rendered frompredictMe.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2022-11-10
Started: 2022-05-14