calcAUC

Based on:
 <a href="https://blog.revolutionanalytics.com/2016/08/roc-curves-in-two-lines-of-code.html">https://blog.revolutionanalytics.com/2016/08/roc-curves-in-two-lines-of-code.html</a>

Succinctly and correctly format statistical summaries of
various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance).
This package also includes empirical tests, such as Monte Carlo and bootstrap distribution estimates.

John Mount

sigr

Succinct and Correct Statistical Summaries for Reports

Nina Zumel

 Win-Vector LLC

calcAUC function

<dl><dt>modelPredictions</dt>
<dd>numeric predictions (not empty), ordered (either increasing or decreasing)</dd>
<dt>yValues</dt>
<dd>truth values (not empty, same length as model predictions)</dd>
<dt>...</dt>
<dd>force later arguments to bind by name.</dd>
<dt>na.rm</dt>
<dd>logical, if TRUE remove NA values.</dd>
<dt>yTarget</dt>
<dd>value considered to be positive.</dd></dl>

Arguments

Based on:
 <a href='https://blog.revolutionanalytics.com/2016/08/roc-curves-in-two-lines-of-code.html'>https://blog.revolutionanalytics.com/2016/08/roc-curves-in-two-lines-of-code.html</a>

calculate AUC. — calcAUC

<dl>

<dt>modelPredictions</dt>
<dd>numeric predictions (not empty), ordered (either increasing or decreasing)</dd>


<dt>yValues</dt>
<dd>truth values (not empty, same length as model predictions)</dd>


<dt>...</dt>
<dd>force later arguments to bind by name.</dd>


<dt>na.rm</dt>
<dd>logical, if TRUE remove NA values.</dd>


<dt>yTarget</dt>
<dd>value considered to be positive.</dd>

</dl>

calcAUC: calculate AUC.

Description

Usage

Value

Arguments

Examples