172 Open source projects that are alternatives of or similar to XGBOD

Anomaly detection related books, papers, videos, and toolboxes

Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

ADRepository: Real-world anomaly detection datasets

(Python, R, C++) Explainable outlier/anomaly detection through decision tree conditioning

Code for reproducing f-AnoGAN in Pytorch

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

TOD: GPU-accelerated Outlier Detection via Tensor Operations

Main component extraction for outlier detection

A scikit-learn compatible library for anomaly detection

List of tools & datasets for anomaly detection on time-series data.

No description or website provided.

Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]

Fairness regulator and rate limiter

Arduino library for identifying outliers with a Hampel filter

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

VisualQC : assistive tool to ease the quality control workflow of neuroimaging data.

Solve many kinds of least-squares and matrix-recovery problems

The Kubervisor allow you to control which pods should receive traffic or not based on anomaly detection.It is a new kind of health check system.

A parallel implementation of local outlier factor based on Spark

A Julia package for robust regressions using M-estimators and quantile regressions

(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

some anomaly detection models and experiments.

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…

The fundamental package for AIops with python.

Python toolbox for transfer learning.

Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

Go implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo.

A Python library for anomaly detection

Open-source framework to detect outliers in Elasticsearch events

Feature Space Singularity for Out-of-Distribution Detection. (SafeAI 2021)

DDC-Outlier: Preventing medication errors using unsupervised learning

Interactive Visualization to Build, Train and Test an Autoencoder with Tensorflow.js

Repository for detecting outliers using Grubb's Threshold & Generalized Extreme Studentized Deviate (ESD) Test

This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

Anomaly detection library based on singular spectrum transformation(sst)

Isolation Forest on Spark

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

anomaly detection by one-class SVM

Pytorch Implementation of DeepLog.

A Ground Mobile Robot Perception Dataset, IEEE RA-L & IEEE T-CYB

Anomaly detection for temporal data using LSTMs

基于智能计算框架nupic的异常检测restful Api.

Log Anomaly Detection - Machine learning to detect abnormal events logs

The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks

Tensorflow implementation of Semi-supervised Sequence Learning (https://arxiv.org/abs/1511.01432)

Hastic data management server for labeling patterns and anomalies in Grafana

Repository for the Deep One-Class Classification ICML 2018 paper

Pytorch implementation of the Loc2Vec with some modifications for speed

A quick and dirty vehicle speed detector using video + anomaly detection

Sherlock is an anomaly detection service built on top of Druid

No description or website provided.

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.