confusion_matrix

Calculates confusion matrix for given cutoff

Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented. Package also supports calculating fairness metrics for regression models. Find more details in (Wiśniewski, Biecek (2021)) <doi:10.48550/arXiv.2104.00507>.

Jakub Wi<c5><9b>niewski

fairmodels

Flexible Tool for Bias Detection, Visualization, and Mitigation

Jakub Wiśniewski

Przemysław Biecek

confusion_matrix function

<dl><dt>probs</dt>
<dd>numeric, vector with probabilities given by model</dd>
<dt>observed</dt>
<dd>numeric, vector with actual values from outcome, either 0 or 1</dd>
<dt>cutoff</dt>
<dd>numeric, single value denoting cutoff/threshold</dd></dl>

Arguments

Confusion matrix — confusion_matrix

<dl>

<dt>probs</dt>
<dd>numeric, vector with probabilities given by model</dd>


<dt>observed</dt>
<dd>numeric, vector with actual values from outcome, either 0 or 1</dd>


<dt>cutoff</dt>
<dd>numeric, single value denoting cutoff/threshold</dd>

</dl>

confusion_matrix: Confusion matrix

Description

Usage

Value

Arguments

Examples