Anomaly Detection Toolkit (ADTK)

Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection.
As the nature of anomaly varies over different cases, a model may not work universally for all anomaly detection problems. Choosing and combining detection algorithms (detectors), feature engineering methods (transformers), and ensemble methods (aggregators) properly is the key to build an effective anomaly detection model.
This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into models. It also provides some functions to process and visualize time series and anomaly events.
Installation
Prerequisites: Python 3.6 or later.
It is recommended to use pip for installation.
pip install adtk
Alternatively, you could install from source code:
git clone https://github.com/arundo/adtk.git
cd adtk/
pip install ./
Examples
Please see Quick Start for a simple example.
For more detailed examples of each module of ADTK, please refer to Examples section in the documentation.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
License
ADTK is licensed under the Mozilla Public License 2.0 (MPL 2.0). See the LICENSE file for details.
文章知识点与官方知识档案匹配,可进一步学习相关知识Python入门技能树首页概览214401 人正在系统学习中 相关资源: 一个用于在时间序列中基于规则/无监督的异常检测的Python工具包–Python开发
声明:本站部分文章及图片源自用户投稿,如本站任何资料有侵权请您尽早请联系jinwei@zod.com.cn进行处理,非常感谢!