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Time Series Anomaly/Changepoint Detection

Packages Description Downloads (pypi)
ADTK Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. Downloads
Alibi Detect Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both TensorFlow and PyTorch backends are supported for drift detection. Downloads
Bayesian Changepoint Detection Bayesian Changepoint Detection package provides methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Downloads
Luminaire Luminaire is a Python package that provides ML-driven solutions for monitoring time series data. Luminaire provides several anomaly detection and forecasting capabilities that incorporate correlational and seasonal patterns as well as uncontrollable variations in the data over time. Downloads
MatrixProfile The Matrix Profile is a novel data structure with corresponding algorithms (stomp, regimes, motifs, etc.) to mine time series data, especially for common pattern extraction and anomalies detection. Downloads
PyOD PyOD is the one of the most comprehensive and scalable Python libraries for detecting outlying objects in multivariate data, which includes more than 40 detection algorithms. Downloads
Ruptures Ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. Downloads
Stumpy STUMPY is a powerful and scalable Python library that efficiently computes something called the matrix profile, which can be used to identify common patterns (motifs) and anomalies. Downloads