dsldDensityByS

Graphs densities of a response variable, grouped by a sensitive variable. 
 Similar to <code>dsldConfounders</code>, but includes sliders to control the 
 bandwidth of the density estimate (analogous to controlling the bin
 width in a histogram).

Statistical and graphical tools for detecting and measuring
discrimination and bias, be it racial, gender, age or other.
Detection and remediation of bias in machine learning algorithms.
'Python' interfaces available.

Norm Matloff

dsld

Data Science Looks at Discrimination

Taha Abdullah

Arjun Ashok

Shubhada Martha

Aditya Mittal

Billy Ouattara

Jonathan Tran

Brandon Zarate Estrada

dsldDensityByS function

<dl> <dt>data</dt>
<dd>Datasetwith at least 1 numerical column and 1 factor column</dd> <dt>cName</dt>
<dd>Possible confounding variable column, an R numeric</dd> <dt>sName</dt>
<dd>Name of the sensitive variable column, an R factor</dd> <dt>graphType</dt>
<dd>Type of graph created. Defaults to "plotly".</dd> <dt>fill</dt>
<dd>To fill the graph. Defaults to "FALSE".</dd></dl>

Arguments

N. Matloff, T. Abdullah, A. Ashok, J. Tran

Author

dsldDensityByS — dsldDensityByS

<dl>

 <dt>data</dt>
<dd>Datasetwith at least 1 numerical column and 1 factor column</dd>

 <dt>cName</dt>
<dd>Possible confounding variable column, an R numeric</dd>

 <dt>sName</dt>
<dd>Name of the sensitive variable column, an R factor</dd>

 <dt>graphType</dt>
<dd>Type of graph created. Defaults to "plotly".</dd>

 <dt>fill</dt>
<dd>To fill the graph. Defaults to "FALSE".</dd>

</dl>

dsldDensityByS: dsldDensityByS

Description

Usage

Value

Arguments

Author

Examples