{"url":"/dataset/tep","name":"TEP","full_name":"Tennessee Eastman Process","description_markdown":"The original paper presented a model of the industrial chemical process named Tennessee Eastman Process and a model-based TEP simulator for data generation. The most widely used benchmark consists of 22 datasets, 21 of which (Fault 1–21) contain faults and 1 (Fault 0) is fault-free. It is available in [repository](https://github.com/YKatser/CPDE/tree/master/TEP_data). All datasets have training (500 samples) and testing (960 samples) parts: training part has healthy state observations, testing part begins right after training, and contains faults which appear after 8 h since the training part. Each dataset has 52 features or observation variables with a 3 min sampling rate for most of all.\r\n\r\nSource: [Unsupervised Offline Changepoint Detection Ensembles](https://www.mdpi.com/2076-3417/11/9/4280#)","description_withheld":null,"homepage":"https://github.com/YKatser/CPDE/tree/master/TEP_data","introduced_date":"1993-01-01","introduced_date_note":null,"introduced_by":null,"license":{"name":"Custom","url":"https://github.com/YKatser/CPDE/tree/master/TEP_data#readme"},"modalities":[{"name":"Time series","url":"/datasets/modality/time-series"}],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"},{"name":"Change Point Detection","url":"/task/change-point-detection","datasets_with_task":"/datasets/task/change-point-detection"}],"languages":[],"variants":["TEP"],"data_loaders":[{"repo":"https://github.com/YKatser/CPDE","url":"https://github.com/YKatser/CPDE/tree/master/TEP_data#readme","frameworks":[]}],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/change-point-detection-on-tep","task":"Change Point Detection","dataset_variant":"TEP","rows":6,"metrics":["NAB (standard)","NAB (lowFP)","NAB (LowFN)"],"first_row_in_archive_order":{"model":"OptEnsemble CPDE algorithm (Min+MinMax/Rank)","paper":"/paper/unsupervised-offline-changepoint-detection","metrics":{"NAB (LowFN)":"42.16","NAB (lowFP)":"41","NAB (standard)":"41.81"},"code_links":[{"title":"YKatser/CPDE","url":"https://github.com/YKatser/CPDE"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/unsupervised-offline-changepoint-detection","title":"Unsupervised Offline Changepoint Detection Ensembles","date":"2021-05-09","rows_on_this_dataset":6,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"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."}