quickOutlier0.1.0 package

Detect and Treat Outliers in Data Mining

detect_density

Detect Density-Based Anomalies (LOF)

detect_multivariate

Detect Multivariate Anomalies (Mahalanobis Distance)

detect_outliers

Detect Anomalies in a Data Frame

plot_outliers

Plot Outliers with ggplot2

scan_data

Scan Entire Dataset for Outliers

treat_outliers

Treat Outliers (Winsorization/Capping)

Download source packageRead PDF manual

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.

  • Maintainer: Daniel López Pérez
  • License: MIT + file LICENSE
  • Last published: 2025-12-19

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