PyOD swMATH ID: 27072 Software Authors: Yue Zhao, Zain Nasrullah, Zheng Li Description: PyOD: A Python Toolbox for Scalable Outlier Detection. PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data. Uniquely, it provides access to a wide range of outlier detection algorithms, including established outlier ensembles and more recent neural network-based approaches, under a single, well-documented API designed for use by both practitioners and researchers. With robustness and scalability in mind, best practices such as unit testing, continuous integration, code coverage, maintainability checks, interactive examples and parallelization are emphasized as core components in the toolbox’s development. PyOD is compatible with both Python 2 and 3 and can be installed through Python Package Index (PyPI) or this https URL https://github.com/yzhao062/pyod. Homepage: https://arxiv.org/abs/1901.01588 Source Code: https://github.com/yzhao062/pyod Dependencies: Python Keywords: Machine Learning; arXiv_cs.LG; arXiv_cs.IR; arXiv_stat.ML; Outlier Detection; Anomaly Detection; Outlier Ensembles; Unsupervised Learning; Neural Networks Related Software: Python; Scikit; PyTorch; TODS; NumPy; PyNomaly; Meta-AAD; LOF; SUOD; PyODDS; Transformers; pandas; Alibi Detect; spaCy; NLTK; TextCL; LSCP; XGBOD; Pigeon; Sparrow Scheduler Cited in: 1 Publication Standard Articles 1 Publication describing the Software Year PyOD: A Python Toolbox for Scalable Outlier Detection Yue Zhao, Zain Nasrullah, Zheng Li 2019 Cited by 3 Authors 1 Cornelis, Chris 1 Lenz, Oliver Urs 1 Theerens, Adnan Cited in 1 Serial 1 International Journal of Approximate Reasoning Cited in 3 Fields 1 Mathematical logic and foundations (03-XX) 1 Measure and integration (28-XX) 1 Computer science (68-XX) Citations by Year