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-4.5)ppsr_0.0.5.zip(r-4.4)ppsr_0.0.5.zip(r-4.3)
ppsr_0.0.5.tgz(r-4.4-any)ppsr_0.0.5.tgz(r-4.3-any)
ppsr_0.0.5.tar.gz(r-4.5-noble)ppsr_0.0.5.tar.gz(r-4.4-noble)
ppsr_0.0.5.tgz(r-4.4-emscripten)ppsr_0.0.5.tgz(r-4.3-emscripten)
ppsr.pdf |ppsr.html
ppsr/json (API)
NEWS

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

Peer review:

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

On CRAN:

4.98 score 74 stars 26 scripts 381 downloads 10 exports 43 dependencies

Last updated 9 months agofrom:8245f33568. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-winNOTENov 14 2024
R-4.5-linuxNOTENov 14 2024
R-4.4-winNOTENov 14 2024
R-4.4-macNOTENov 14 2024
R-4.3-winNOTENov 14 2024
R-4.3-macNOTENov 14 2024

Exports:available_algorithmsavailable_evaluation_metricsscorescore_correlationsscore_dfscore_matrixscore_predictorsvisualize_bothvisualize_correlationsvisualize_pps

Dependencies:clicodetoolscolorspacecpp11dplyrfansifarvergenericsggplot2globalsgluegridExtragtablehardhatisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmeparsnippillarpkgconfigprettyunitspurrrR6RColorBrewerrlangrpartscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

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