{"id":34044835,"url":"https://github.com/patrickzib/dictionary","last_synced_at":"2026-04-08T12:02:28.622Z","repository":{"id":65575168,"uuid":"583620135","full_name":"patrickzib/dictionary","owner":"patrickzib","description":"WEASEL 2.0 - A Random Dilated Dictionary Transform for Fast, Accurate and Constrained Memory Time Series Classification","archived":false,"fork":false,"pushed_at":"2025-05-05T07:12:26.000Z","size":8822,"stargazers_count":17,"open_issues_count":0,"forks_count":4,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-02-21T16:44:57.762Z","etag":null,"topics":["classification","dictionary","supervised-learning","time-series","time-series-classification","timeseries"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/patrickzib.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2022-12-30T10:49:03.000Z","updated_at":"2026-01-20T13:52:55.000Z","dependencies_parsed_at":"2024-09-13T00:34:59.116Z","dependency_job_id":"1d0c23c7-dc14-4b4a-ac4d-bd58a8a3923a","html_url":"https://github.com/patrickzib/dictionary","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/patrickzib/dictionary","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/patrickzib%2Fdictionary","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/patrickzib%2Fdictionary/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/patrickzib%2Fdictionary/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/patrickzib%2Fdictionary/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/patrickzib","download_url":"https://codeload.github.com/patrickzib/dictionary/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/patrickzib%2Fdictionary/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31554110,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-08T10:21:54.569Z","status":"ssl_error","status_checked_at":"2026-04-08T10:21:38.171Z","response_time":54,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["classification","dictionary","supervised-learning","time-series","time-series-classification","timeseries"],"created_at":"2025-12-13T23:02:43.378Z","updated_at":"2026-04-08T12:02:28.557Z","avatar_url":"https://github.com/patrickzib.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# WEASEL 2.0 - A Random Dilated Dictionary Transform for Fast, Accurate and Memory Constrained Time Series Classification\n\nWEASEL 2.0 combines a novel dilation mapping, small dictionaries and hyper-parameter ensembling to obtain a fast, accurate, and constrained memory TSC. WEASEL 2.0 is significantly more accurate than its predecessor dictionary methods (BOSS, TDE, WEASEL), and in the same group as SotA non-ensemble methods. \n\nArXiv-Paper: https://arxiv.org/abs/2301.10194\n\nThe paper has been accepted within the journal track at ECML-PKDD 2023: https://link.springer.com/article/10.1007/s10994-023-06395-w\n \n### Accuracy against dictionary classifiers\n![UCR_accuracy_subset](https://user-images.githubusercontent.com/7783034/214376239-0115e87e-e426-45fc-8f70-1684989745cc.png)\n\n### Accuracy against SotA classifiers\n![UCR_accuracy](https://user-images.githubusercontent.com/7783034/214376249-51f49c4a-1691-4d12-97e0-3d6ade7de4e3.png)\n\n### Runtime against SotA classifiers\n![UCR_runtime](https://user-images.githubusercontent.com/7783034/214376264-7961db3b-2f24-488f-abbc-d53433ffacbc.png)\n\n\n## Installation\n\n### Dependencies\n```\naeon \u003e= 0.1.0\n```\n\n# Installation\n\nThe easiest is to use pip to install weasel-classifier.\n\n## a) Install using pip\n```\npip install weasel-classifier\n```\n\nYou can also install  the project from source.\n\n## b) Build from Source\n\nFirst, download the repository.\n```\ngit clone https://github.com/patrickzib/dictionary.git\n```\n\nChange into the directory and build the package from source.\n```\npip install .\n```\n\n\n### Train a WEASEL 2.0 classifier\n\nWEASEL v2 follows the aeon pipeline.\n\n```python\nfrom aeon.datasets import load_arrow_head\nfrom weasel.classification.dictionary_based import WEASEL_V2\n\nX_train, y_train = load_arrow_head(split=\"train\", return_type=\"numpy3d\")\nX_test, y_test = load_arrow_head(split=\"test\", return_type=\"numpy3d\")\nclf = WEASEL_V2(random_state=1379, n_jobs=4)\nclf.fit(X_train,y_train)\nclf.predict(X_test)\n```\n\n\n## AEON\n\nWEASEL v2 is part of the `aeon` toolkit, too: https://github.com/aeon-toolkit/aeon\n\n\n## Citing\n\nIf you use this algorithm or publication, please cite:\n\n```bibtex\n@article{schaefer2023weasel,\n  title={WEASEL 2.0: a random dilated dictionary transform for fast, accurate and memory constrained time series classification},\n  author={Sch{\\\"a}fer, Patrick and Leser, Ulf},\n  journal={Machine Learning},\n  volume={112},\n  number={12},\n  pages={4763--4788},\n  year={2023},\n  publisher={Springer}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpatrickzib%2Fdictionary","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpatrickzib%2Fdictionary","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpatrickzib%2Fdictionary/lists"}