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quickOutlier (version 0.1.0)

Detect and Treat Outliers in Data Mining

Description

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.

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Install

install.packages('quickOutlier')

Version

0.1.0

License

MIT + file LICENSE

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Maintainer

Daniel López Pérez

Last Published

December 19th, 2025

Functions in quickOutlier (0.1.0)

plot_outliers

Plot Outliers with ggplot2
detect_outliers

Detect Anomalies in a Data Frame
scan_data

Scan Entire Dataset for Outliers
detect_density

Detect Density-Based Anomalies (LOF)
detect_multivariate

Detect Multivariate Anomalies (Mahalanobis Distance)
treat_outliers

Treat Outliers (Winsorization/Capping)