Outlier

Discover relevant subspaces: subsets of features that let you most effectively perform outlier detection on tabular dataThis text is a component of a series related to the challenges, and the techniques that could be...

Using well-crafted synthetic data to check and evaluate outlier detectorsThis text continues my series on outlier detection, following articles on Counts Outlier Detector and Frequent Patterns Outlier Factor, and provides one other excerpt from...

If it really works, keep it easyAs everyone knows, a giant a part of a knowledge scientist’s job is to wash and preprocess data. An enormous a part of this involves outlier detection and...

Using batting stats from Major League Baseball’s 2023 seasonOutlier detection is an unsupervised machine learning task to discover anomalies (unusual observations) inside a given data set. This task is useful in lots of real-world...

Learn detect outliers using Probability Density Functions for fast and light-weight models and explainable results.