Package: effectplots 0.2.3
effectplots: Effect Plots
High-performance implementation of various effect plots useful for regression and probabilistic classification tasks. The package includes partial dependence plots (Friedman, 2021, <doi:10.1214/aos/1013203451>), accumulated local effect plots and M-plots (both from Apley and Zhu, 2016, <doi:10.1111/rssb.12377>), as well as plots that describe the statistical associations between model response and features. It supports visualizations with either 'ggplot2' or 'plotly', and is compatible with most models, including 'Tidymodels', models wrapped in 'DALEX' explainers, or models with case weights.
Authors:
effectplots_0.2.3.tar.gz
effectplots_0.2.3.zip(r-4.7)effectplots_0.2.3.zip(r-4.6)effectplots_0.2.3.zip(r-4.5)
effectplots_0.2.3.tgz(r-4.6-x86_64)effectplots_0.2.3.tgz(r-4.6-arm64)effectplots_0.2.3.tgz(r-4.5-x86_64)effectplots_0.2.3.tgz(r-4.5-arm64)
effectplots_0.2.3.tar.gz(r-4.7-arm64)effectplots_0.2.3.tar.gz(r-4.7-x86_64)effectplots_0.2.3.tar.gz(r-4.6-arm64)effectplots_0.2.3.tar.gz(r-4.6-x86_64)
effectplots_0.2.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
effectplots/json (API)
NEWS
| # Install 'effectplots' in R: |
| install.packages('effectplots', repos = c('https://mayer79.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mayer79/effectplots/issues
machine-learningregressionxaicpp
Last updated from:a1b1624226. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 177 | ||
| linux-devel-x86_64 | OK | 188 | ||
| source / vignettes | OK | 194 | ||
| linux-release-arm64 | OK | 176 | ||
| linux-release-x86_64 | OK | 156 | ||
| macos-release-arm64 | OK | 208 | ||
| macos-release-x86_64 | OK | 327 | ||
| macos-oldrel-arm64 | OK | 257 | ||
| macos-oldrel-x86_64 | OK | 491 | ||
| windows-devel | OK | 133 | ||
| windows-release | OK | 152 | ||
| windows-oldrel | OK | 131 | ||
| wasm-release | OK | 131 |
Exports:.ale.pdaleaverage_observedaverage_predictedbiaseffect_importancefcutfeature_effectspartial_dependence
Dependencies:askpassbase64encbslibcachemclicollapsecpp11crosstalkcurldata.tabledigestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlazyevallifecyclemagrittrmemoisemimeopensslotelpatchworkpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownS7sassscalesstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Barebone Accumulated Local Effects (ALE) | .ale |
| Barebone Partial Dependence | .pd |
| Accumulated Local Effects (ALE) | ale ale.default ale.explainer ale.H2OModel ale.ranger |
| Average Observed | average_observed |
| Average Predictions | average_predicted |
| Bias / Average Residuals | bias |
| Variable Importance | effect_importance |
| Fast cut() | fcut |
| Feature Effects | feature_effects feature_effects.default feature_effects.explainer feature_effects.H2OModel feature_effects.ranger |
| Partial Dependence | partial_dependence partial_dependence.default partial_dependence.explainer partial_dependence.H2OModel partial_dependence.ranger |
| Plots "EffectData" Object | plot.EffectData |
| Update "EffectData" Object | update.EffectData |
