About the study In the present study, researchers applied outlier detection to different SARS-CoV-2 nucleotide sequences before and after the emergence of a novel variant.

Grafana has released outlier detection as part of their Grafana Machine Learning toolkit. Outlier detection can be used to monitor a group of similar things and be alerted when some of them start ...

Dehan Kong, Howard D. Bondell, Yichao Wu, FULLY EFFICIENT ROBUST ESTIMATION, OUTLIER DETECTION AND VARIABLE SELECTION VIA PENALIZED REGRESSION, Statistica Sinica, Vol. 28, No. 2, Computer Experiments ...

Explore the importance of robust statistics like median and MAD in data analysis, ensuring accurate insights despite outliers ...

Robust estimation and outlier detection play a critical role in modern data analysis, particularly when dealing with high-dimensional datasets.

Timothy E. Smetek, Kenneth W. Bauer Jr., A Comparison of Multivariate Outlier Detection Methods For Finding Hyperspectral Anomalies, Military Operations Research, Vol ...

In this article, the authors discuss how to detect fraud in credit card transactions, using supervised machine learning algorithms (random forest, logistic regression) as well as outlier detection ...

Recent bank failures point to the continuing need for vigilance by regulators and investors. Now, a report in the International Journal of Operational Research, discusses the possibility of an ...