plot_interactive

Generates an interactive scatter plot using 'plotly'. Outliers detected by the specified
method are highlighted in red.

Implements a suite of tools for outlier detection and treatment
in data mining. It includes univariate methods (Z-score, Interquartile Range),
multivariate detection using Mahalanobis distance, and density-based
detection (Local Outlier Factor) via the 'dbscan' package. It also
provides functions for visualization using 'ggplot2' and data cleaning
via Winsorization.

Daniel López Pérez

quickOutlier

Detect and Treat Outliers in Data Mining

plot_interactive function

<dl><dt>data</dt>
<dd>A data frame.</dd>
<dt>x_col</dt>
<dd>The name of the numeric column for the X-axis.</dd>
<dt>y_col</dt>
<dd>The name of the numeric column for the Y-axis.</dd>
<dt>confidence_level</dt>
<dd>Numeric. Threshold for detection (0.95, 0.99). Lower values make detection stricter.</dd></dl>

Arguments

Create an Interactive Outlier Plot — plot_interactive

<dl>

<dt>data</dt>
<dd>A data frame.</dd>


<dt>x_col</dt>
<dd>The name of the numeric column for the X-axis.</dd>


<dt>y_col</dt>
<dd>The name of the numeric column for the Y-axis.</dd>


<dt>confidence_level</dt>
<dd>Numeric. Threshold for detection (0.95, 0.99). Lower values make detection stricter.</dd>

</dl>

plot_interactive: Create an Interactive Outlier Plot

Description

Usage

Value

Arguments