Welcome to TSBenchmark

TSBenchmark is a distributed benchmark framework specified for time series forecasting tasks using automated machine learning (AutoML) algorithms.

TSBenchmark supports both time series and AutoML characteristics.

As for time series forecasting, it supports univariate forecasting, multivariate forecasting, as well as covariate benchmark. During operation, it collects the information of optimal parameter combinations, performance indicators and other key parameters, supporting the analysis and evaluation of the AutoML framework.

This benchmark framework supports distributed operation mode and shows high scores in efficiency ranking. It integrates the lightweight distributed scheduling framework in hypernets and can be executed in both Python and CONDA virtual environments. For the purpose of environment isolation, it is recommended to use CONDA as the environment manager to support different algorithms.

Content:

• Concepts
• Quick start
• Examples
  • Custom Player Examples
  • Benchmark Examples
• API reference
  • tsbenchmark package
• Release Notes
  • version 0.1.0

Indices and tables

• Index

• Module Index

• Search Page

TSBenchmark is an open source project created by DataCanvas .