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quickOutlier  

Detect and Treat Outliers in Data Mining
View on CRAN: Click here


Download and install quickOutlier package within the R console
Install from CRAN:
install.packages("quickOutlier")

Install from Github:
library("remotes")
install_github("cran/quickOutlier")

Install by package version:
library("remotes")
install_version("quickOutlier", "0.1.0")



Attach the package and use:
library("quickOutlier")
Maintained by
Daniel López Pérez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-19
Latest Update: 2025-12-19
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.
How to cite:
Daniel López Pérez (2025). quickOutlier: Detect and Treat Outliers in Data Mining. R package version 0.1.0, https://cran.r-project.org/web/packages/quickOutlier. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.1.0 (2025-12-19 16:00)
Other packages that cited quickOutlier R package
View quickOutlier citation profile
Other R packages that quickOutlier depends, imports, suggests or enhances
Complete documentation for quickOutlier
Functions, R codes and Examples using the quickOutlier R package
Full quickOutlier package functions and examples
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