About this document
Outlier Detection Methods Explained by nandini.slytherin is a document available to read on EtoBox.
The document outlines various outlier detection methods categorized into supervised, unsupervised, and semi-supervised approaches. Supervised methods utilize labeled data for classification, while unsupervised methods identify outliers without labels, often using clustering techniques. Semi-supervised methods leverage limited labeled data alongside a larger set of unlabeled data to detect deviations from normal patterns.
- Author
- nandini.slytherin
- Language
- EN