SUOD
Outlier Detector Framework
A Python framework for accelerating large-scale unsupervised outlier detection in heterogeneous datasets
(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)
380 stars
17 watching
49 forks
Language: Python
last commit: 10 months ago
Linked from 1 awesome list
anomaly-detectiondata-miningdistributed-systemsknowledge-distillationmachine-learningmachine-learning-algorithmsmachine-learning-libraryoutlier-detectionpython
ethicalml/awesome-production-machine-learningRelated projects:
| Repository | Description | Stars |
|---|---|---|
 datamllab/pyodds | An end-to-end outlier detection system that integrates machine learning algorithms with database support | 252 |
 pygod-team/pygod | Detects anomalies in graph data using various algorithms | 1,336 |
| datamllab/tods | An automated system for detecting outliers in time-series data using machine learning algorithms and human expertise. | 1,459 |
 seldonio/alibi-detect | A Python library for detecting outliers, adversarial examples, and data drift in various types of data | 2,247 |
 eaglelab-zju/dgld | An open-source library for training and evaluating graph anomaly detection models | 64 |
 safe-graph/ugfraud | A toolbox for unsupervised graph-based fraud detection using multiple algorithms and techniques | 129 |
 shiyuliang/odin-pytorch | An implementation of a method for detecting out-of-distribution examples in neural networks | 200 |
 arundo/adtk | A toolkit for rule-based and unsupervised anomaly detection in time series data | 1,098 |
 iqiukp/svdd-matlab | A MATLAB implementation of Support Vector Data Description (SVDD) for anomaly detection and classification. | 78 |
| safe-graph/dgfraud | A toolbox for building and comparing graph neural network-based fraud detection models | 693 |
 eth-sri/bayes-framework-leakage | Develops and evaluates a framework for detecting attacks on federated learning systems | 11 |
 business-science/anomalize | A package providing functions to decompose and detect anomalies in time series data | 339 |
 junyangwang0410/haelm | A framework for detecting hallucinations in large language models | 17 |
 jxr326/swinmcnet | A Python-based object detection framework utilizing transformers and computer vision techniques to detect salient objects in RGB-thermal images | 16 |
 szq0214/dsod | A deep learning-based object detection system from scratch | 706 |