german

<code>german</code> dataset. Data contains information about people and their credit risks.

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)) <arXiv:2104.00507>.

Jakub Wi<c5><9b>niewski

fairmodels

Flexible Tool for Bias Detection, Visualization, and Mitigation

Jakub Wiśniewski

Przemysław Biecek

german function

A data frame with 1000 rows and 10 variables:<dl>
 <dt>Risk</dt>
<dd>factor, good/bad risk connected with giving the credit. Models should predict this values</dd> <dt>Sex</dt>
<dd>factor, male/female , considered to be protected group</dd> <dt>Job</dt>
<dd>numeric, job titles converted to integers where 0- unemployed/unskilled, 3- management/ self-employed/highly qualified employee/ officer</dd> <dt>Housing</dt>
<dd>factor, rent/own/free where this person lives</dd> <dt>Saving.accounts</dt>
<dd>factor, little/moderate/quite rich/rich/not_known, where not_known indicates NA</dd> <dt>Checking.account</dt>
<dd>factor, little/moderate/rich/not_known, where not_known indicates NA</dd> <dt>Credit.amount</dt>
<dd>numeric, amount of money in credit</dd> <dt>Duration</dt>
<dd>numeric, duration of credit</dd> <dt>Purpose</dt>
<dd>factor, purpose of credit</dd> <dt>Age</dt>
<dd>numeric, age of person that applied for credit</dd>
</dl>

Format

Modified German Credit data dataset — german

A data frame with 1000 rows and 10 variables:<dl>
 <dt>Risk</dt>
<dd>factor, good/bad risk connected with giving the credit. Models should predict this values</dd>

 <dt>Sex</dt>
<dd>factor, male/female , considered to be protected group</dd>

 <dt>Job</dt>
<dd>numeric, job titles converted to integers where 0- unemployed/unskilled, 3- management/ self-employed/highly qualified employee/ officer</dd>

 <dt>Housing</dt>
<dd>factor, rent/own/free where this person lives</dd>

 <dt>Saving.accounts</dt>
<dd>factor, little/moderate/quite rich/rich/not_known, where not_known indicates NA</dd>

 <dt>Checking.account</dt>
<dd>factor, little/moderate/rich/not_known, where not_known indicates NA</dd>

 <dt>Credit.amount</dt>
<dd>numeric, amount of money in credit</dd>

 <dt>Duration</dt>
<dd>numeric, duration of credit</dd>

 <dt>Purpose</dt>
<dd>factor, purpose of credit</dd>

 <dt>Age</dt>
<dd>numeric, age of person that applied for credit</dd>


</dl>

german: Modified German Credit data dataset

Description

Usage

Arguments

Format