{"url":"/dataset/tssb","name":"TSSB","full_name":"Time Series Segmentation Benchmark","description_markdown":"The time series segmentation benchmark (TSSB) currently contains 75 annotated time series (TS) with 1-9 segments. Each TS is constructed from one of the UEA & UCR time series classification datasets. We group TS by label and concatenate them to create segments with distinctive temporal patterns and statistical properties. We annotate the offsets at which we concatenated the segments as change points (CPs). Addtionally, we apply resampling to control the dataset resolution and add approximate, hand-selected window sizes that are able to capture temporal patterns.","description_withheld":null,"homepage":"https://github.com/ermshaua/time-series-segmentation-benchmark","introduced_date":"2021-10-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/clasp-time-series-segmentation","title":"ClaSP - Time Series Segmentation","first_author":"Patrick Schäfer","url":null},"license":{"name":"BSD-3-Clause License","url":"https://github.com/ermshaua/time-series-segmentation-benchmark/blob/main/LICENSE"},"modalities":[{"name":"Time series","url":"/datasets/modality/time-series"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Time Series Analysis","url":"/task/time-series","datasets_with_task":"/datasets/task/time-series"},{"name":"Change Point Detection","url":"/task/change-point-detection","datasets_with_task":"/datasets/task/change-point-detection"}],"languages":[],"variants":["TSSB"],"data_loaders":[{"repo":"https://github.com/ermshaua/claspy","url":"https://github.com/ermshaua/claspy","frameworks":[]},{"repo":"https://github.com/ermshaua/time-series-segmentation-benchmark","url":"https://github.com/ermshaua/time-series-segmentation-benchmark","frameworks":[]}],"num_papers_in_archive":9,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/change-point-detection-on-tssb","task":"Change Point Detection","dataset_variant":"TSSB","rows":4,"metrics":["Relative Change Point Distance","Covering"],"first_row_in_archive_order":{"model":"ClaSP","paper":"/paper/clasp-time-series-segmentation","metrics":{"Relative Change Point Distance":"0.0073"},"code_links":[{"title":"ermshaua/claspy","url":"https://github.com/ermshaua/claspy"},{"title":"ermshaua/time-series-segmentation-benchmark","url":"https://github.com/ermshaua/time-series-segmentation-benchmark"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/clasp-parameter-free-time-series-segmentation","title":"ClaSP -- Parameter-free Time Series Segmentation","date":"2022-07-28","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/clasp-time-series-segmentation","title":"ClaSP - Time Series Segmentation","date":"2021-10-26","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/espresso-entropy-and-shape-aware-time-series","title":"ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data","date":"2020-07-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bayesian-online-changepoint-detection","title":"Bayesian Online Changepoint Detection","date":"2007-10-19","rows_on_this_dataset":1,"code_links":8,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":17,"samples_ran":2,"samples_unverified":15,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":17,"samples_ran":2,"samples_unverified":15,"pointer_only_for_licence":3,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}