score_correlations

Calculate correlation coefficients for whole dataframe

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>.

Paul van der Laken

ppsr

Predictive Power Score

score_correlations function

<dl><dt>df</dt>
<dd>data.frame containing columns for x and y</dd>
<dt>...</dt>
<dd>arguments to pass to <code><a href="/link/stats%3A%3Acor()?package=ppsr&version=0.0.5" data-mini-rdoc="ppsr::stats::cor()">stats::cor()</a></code></dd></dl>

Arguments

Calculate correlation coefficients for whole dataframe — score_correlations

<dl>

<dt>df</dt>
<dd>data.frame containing columns for x and y</dd>


<dt>...</dt>
<dd>arguments to pass to <code><a href='https://rdrr.io/r/stats/cor.html'>stats::cor()</a></code></dd>

</dl>

score_correlations: Calculate correlation coefficients for whole dataframe

Description

Usage

Value

Arguments

Examples