detect_categorical_outliers

Identifies categories in a character or factor vector that appear less frequently
than a specified threshold.

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

detect_categorical_outliers function

<dl><dt>data</dt>
<dd>A vector (character or factor).</dd>
<dt>min_freq</dt>
<dd>Numeric. The minimum percentage (0 to 1) required to be considered normal.
Defaults to 0.01 (1 percent).</dd></dl>

Arguments

Detect Rare Categories (Categorical Outliers) — detect_categorical_outliers

<dl>

<dt>data</dt>
<dd>A vector (character or factor).</dd>


<dt>min_freq</dt>
<dd>Numeric. The minimum percentage (0 to 1) required to be considered normal.
Defaults to 0.01 (1 percent).</dd>

</dl>

detect_categorical_outliers: Detect Rare Categories (Categorical Outliers)

Description

Usage

Value

Arguments

Details

Examples