Multiverse Archive loaders and utilities for MTSC benchmarks.
Project description
Welcome to the Multiverse |
The archive and benchmark repository for multivariate time series classification.
Datasets · Results · Leaderboard · Experiments · Classifiers · Contributing
The Multiverse is a new archive of multivariate time series classification datasets. This repository is for accessing, benchmarking, and extending this new archive.
It brings together datasets, published results, reproducible evaluation workflows, and leaderboard infrastructure in one place. The aim is to make it easier to:
- access benchmark datasets for multivariate time series classification,
- load data into Python workflows,
- explore and compare against published results,
- reproduce baseline experiments,
- evaluate new classifiers consistently,
- and contribute new algorithms and results back to the archive.
This repository is intended as both a practical resource for researchers and a public record of benchmark results.
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Quick start
Load a dataset
Use the examples in examples/aeon_quickstart.py as a starting point for downloading and loading Multiverse datasets.
Run an experiment
To reproduce a benchmark run or evaluate a new classifier, start from:
Explore the results
Browse the generated leaderboard views in:
Donate your code and published results
For submission layout and result schema, see:
Repository layout
multiverse/
├── docs/ # Documentation
├── experiments/ # Benchmark and reproduction scripts
├── results/ # Submitted results and schema
└── src/ # Python package source for classifiers
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