Description
Scores of Nominal Outlyingness (SONO).
Description
Computes scores of outlyingness for data sets consisting of nominal variables and includes various evaluation metrics for assessing performance of outlier identification algorithms producing scores of outlyingness. The scores of nominal outlyingness are computed based on the framework of Costa and Papatsouma (2025) <doi:10.48550/arXiv.2408.07463>.
README.md
SONO (Scores Of Nominal Outlyingness) 
The SONO (Scores Of Nominal Outlyingness) R package includes a function that can be used for detecting outliers in data sets consisting of nominal data. Some of the capabilities of the package include:
- Calculating scores of outlyingness for data sets consisting of nominal variables.
- Estimating the maximum length of nominal sequences (MAXLEN) for doing frequent pattern mining.
- Computing maximum/minimum itemset support threshold values.
- Visualising the matrix of variable contributions to the score of nominal outlyingness computed.
- Computing evaluation metrics to compare performance of outlier detection algorithms (ROC AUC, Recall@K, Average Outlier Rank).
A detailed description of the methods included in the package can be found in Costa, E., & Papatsouma, I. (2025). A novel framework for quantifying nominal outlyingness.
Installation
The package is available on CRAN and can therefore be installed using the following:
install.packages("SONO")
The package can also be installed directly from GitHub using devtools.
# install.packages("devtools")
devtools::install_github('EfthymiosCosta/SONO')