The PPS is an asymmetric, data-type-agnostic score that can detect linear or non-linear relationships between two columns. The score ranges from 0 (no predictive power) to 1 (perfect predictive power). It can be useful for data exploration purposes, in the same way correlation analysis is. For more information on PPS, see Wetschoreck (2020) <https://towardsdatascience.com/rip-correlation-introducing-the-predictive-power-score-3d90808b9598> or github <https://github.com/paulvanderlaken/ppsr>.
Version: | 0.0.2 |
Imports: | ggplot2 (≥ 3.3.3), parsnip (≥ 0.1.5), rpart (≥ 4.1.15), withr (≥ 2.4.1), gridExtra (≥ 2.3), parallel (≥ 4.0.3) |
Suggests: | testthat (≥ 2.0.0) |
Published: | 2021-03-02 |
Author: | Paul van der Laken [aut, cre] |
Maintainer: | Paul van der Laken <paulvanderlaken at gmail.com> |
License: | GPL (≥ 3) |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | ppsr results |
Reference manual: | ppsr.pdf |
Package source: | ppsr_0.0.2.tar.gz |
Windows binaries: | r-devel: ppsr_0.0.2.zip, r-release: ppsr_0.0.2.zip, r-oldrel: ppsr_0.0.2.zip |
macOS binaries: | r-release (arm64): ppsr_0.0.2.tgz, r-oldrel (arm64): ppsr_0.0.2.tgz, r-release (x86_64): ppsr_0.0.2.tgz, r-oldrel (x86_64): ppsr_0.0.2.tgz |
Reverse suggests: | dlookr |
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