We present TODS, an automated Time Series Outlier Detection System for research and industrial applications. TODS is a highly modular system that supports easy pipeline construction. The basic building block of TODS is primitive, which is an implementation of a function with hyperparameters. TODS currently supports 70 primitives, including data processing, time series processing, feature analysis, detection algorithms, and a reinforcement module. Users can freely construct a pipeline using these primitives and perform end- to-end outlier detection with the constructed pipeline. TODS provides a Graphical User Interface (GUI), where users can flexibly design a pipeline with drag-and-drop. Moreover, a data-driven searcher is provided to automatically discover the most suitable pipelines given a dataset. TODS is released under Apache 2.0 license at https://github.com/datamllab/tods.

中文翻译：

---

TODS：自动时间序列异常值检测系统

我们展示了 TODS，这是一种用于研究和工业应用的自动化时间序列异常值检测系统。TODS 是一个高度模块化的系统，支持简单的管道建设。TODS 的基本构建块是原始的，它是具有超参数的函数的实现。TODS 目前支持 70 种原语，包括数据处理、时间序列处理、特征分析、检测算法和一个强化模块。用户可以使用这些原语自由构建管道，并使用构建的管道执行端到端异常值检测。TODS 提供图形用户界面 (GUI)，用户可以在其中灵活地通过拖放来设计管道。此外，提供了一个数据驱动的搜索器来自动发现给定数据集的最合适的管道。TODS 在 Apache 2 下发布。