quickOutlier
Detect and Treat Outliers in Data Mining
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.5 |
rolling linux/jammy R-4.5 | quickOutlier_0.1.5.tar.gz |
1.2 MiB |
0.1.5 |
rolling linux/noble R-4.5 | quickOutlier_0.1.5.tar.gz |
1.2 MiB |
0.1.5 |
rolling source/ R- | quickOutlier_0.1.5.tar.gz |
1.1 MiB |
0.1.5 |
latest linux/jammy R-4.5 | quickOutlier_0.1.5.tar.gz |
1.2 MiB |
0.1.5 |
latest linux/noble R-4.5 | quickOutlier_0.1.5.tar.gz |
1.2 MiB |
0.1.5 |
latest source/ R- | quickOutlier_0.1.5.tar.gz |
1.1 MiB |
0.1.5 |
2026-04-26 source/ R- | quickOutlier_0.1.5.tar.gz |
1.1 MiB |
0.1.5 |
2026-04-23 source/ R- | quickOutlier_0.1.5.tar.gz |
1.1 MiB |
0.1.5 |
2026-04-09 windows/windows R-4.5 | quickOutlier_0.1.5.zip |
1.2 MiB |