Package: ppsr 0.0.5

ppsr: Predictive Power Score

The Predictive Power Score (PPS) is an asymmetric, data-type-agnostic score that can detect linear or non-linear relationships between two variables. The score ranges from 0 (no predictive power) to 1 (perfect predictive power). PPS can be useful for data exploration purposes, in the same way correlation analysis is. For more information on PPS, see <https://github.com/paulvanderlaken/ppsr>.

Authors:Paul van der Laken [aut, cre, cph]

ppsr_0.0.5.tar.gz
ppsr_0.0.5.zip(r-4.7)ppsr_0.0.5.zip(r-4.6)ppsr_0.0.5.zip(r-4.5)
ppsr_0.0.5.tgz(r-4.6-any)ppsr_0.0.5.tgz(r-4.5-any)
ppsr_0.0.5.tar.gz(r-4.7-any)ppsr_0.0.5.tar.gz(r-4.6-any)
ppsr_0.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ppsr/json (API)
NEWS

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

Bug tracker:https://github.com/paulvanderlaken/ppsr/issues

On CRAN:

Conda:

4.99 score 75 stars 26 scripts 386 downloads 10 exports 37 dependencies

Last updated from:8245f33568. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE121
source / vignettesOK205
linux-release-x86_64NOTE117
macos-release-arm64NOTE144
macos-oldrel-arm64NOTE183
windows-develNOTE85
windows-releaseNOTE76
windows-oldrelNOTE76
wasm-releaseOK103

Exports:available_algorithmsavailable_evaluation_metricsscorescore_correlationsscore_dfscore_matrixscore_predictorsvisualize_bothvisualize_correlationsvisualize_pps

Dependencies:clicodetoolscpp11dplyrfarvergenericsggplot2globalsgluegridExtragtablehardhatisobandlabelinglifecyclemagrittrparsnippillarpkgconfigprettyunitspurrrR6RColorBrewerrlangrpartS7scalessparsevctrsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Lists all algorithms currently supportedavailable_algorithms
Lists all evaluation metrics currently supportedavailable_evaluation_metrics
Normalizes the original score compared to a naive baseline score The calculation that's being performed depends on the type of modelnormalize_score
ppsr: An R implementation of the Predictive Power Score (PPS)ppsr-package ppsr
Calculate predictive power score for x on yscore
Calculate correlation coefficients for whole dataframescore_correlations
Calculate predictive power scores for whole dataframe Iterates through the columns of the dataframe, calculating the predictive power score for every possible combination of 'x' and 'y'.score_df
Calculate predictive power score matrix Iterates through the columns of the dataset, calculating the predictive power score for every possible combination of 'x' and 'y'.score_matrix
Calculates out-of-sample model performance of a statistical modelscore_model
Calculate out-of-sample model performance of naive baseline model The calculation that's being performed depends on the type of model For regression models, the mean is used as prediction For classification, a model predicting random values and a model predicting modal values are used and the best model is taken as baseline scorescore_naive
Calculate predictive power scores for y Calculates the predictive power scores for the specified 'y' variable using every column in the dataset as 'x', including itself.score_predictors
Visualize the PPS & correlation matricesvisualize_both
Visualize the correlation matrixvisualize_correlations
Visualize the Predictive Power scores of the entire dataframe, or given a targetvisualize_pps