score_matrix

Note that the targets are on the rows, and the features on the columns.

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_matrix function

<dl><dt>df</dt>
<dd>data.frame containing columns for x and y</dd>
<dt>...</dt>
<dd>any arguments passed to <code>score_df</code>,
some of which will be passed on to <code>score</code></dd></dl>

Arguments

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

<dl>

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


<dt>...</dt>
<dd>any arguments passed to <code>score_df</code>,
some of which will be passed on to <code>score</code></dd>

</dl>

Calculate predictive power score matrix
Iterates through the columns of the dataset, calculating the predictive power
score for every possible combination of <code>x</code> and <code>y</code>.

score_matrix: 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`.

Description

Usage

Value

Arguments

Examples