Welcome to PyOD, a comprehensive but easy-to-use Python library for detecting anomalies in multivariate data. Whether you are working with a small-scale project or large datasets, PyOD …

PyOD, established in 2017, has become a go-to Python library for detecting anomalous/outlying objects in multivariate data. This exciting yet challenging field is commonly referred to as Outlier Detection or …

Dec 2, 2025 · PyOD, established in 2017, has become a go-to Python library for detecting anomalous/outlying objects in multivariate data. This exciting yet challenging field is commonly …

Dec 11, 2024 · We introduced PyOD 2, a significant update to the PyOD library, emphasizing integrating state-of-the-art deep learning models under a unified PyTorch framework and introducing a large …

PyOD is the most comprehensive and scalable Python library for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as Outlier Detection or …

Oct 16, 2024 · In this article, we will explore how to detect outliers using the PyOD library, focusing on the Iris dataset. Why Use PyOD? PyOD (Python Outlier Detection) is a comprehensive library …

Nov 16, 2025 · pyod is A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection). It's one of the most widely used packages in the Python ecosystem for developers …

For an observation, the variance of its weighted cosine scores to all neighbors could be viewed as the outlying score. See [BKZ+08] for details. Two version of ABOD are supported: Fast ABOD: use k …

PyOD is an open-source Python toolbox for performing scalable outlier detection on multi-variate data.

PyOD toolkit consists of three major groups of functionalities: (i) outlier detection algorithms; (ii) outlier ensemble frameworks and (iii) outlier detection utility functions.