{
  "video_id": "reddit_1w1wt1s",
  "channel_slug": "MachineLearning",
  "channel_handle": "r/MachineLearning",
  "title": "You can beat SOTA Time Series Anomaly Detection methods with a 100 year old algorithm [R]",
  "url": "https://www.reddit.com/r/MachineLearning/comments/1w1wt1s/you_can_beat_sota_time_series_anomaly_detection/",
  "external_url": null,
  "upload_date": "20260829",
  "published_at": "2026-08-29T20:16:17+00:00",
  "transcript": "[You can beat SOTA Time Series Anomaly Detection methods with a 100 year old algorithm](https://preview.redd.it/y2ez5kvccdmh1.jpg?width=2859&format=pjpg&auto=webp&s=3f80362f7124fab5cfe5d2798746d68e637bce13)\n\n\n\nTime Series Anomaly Detection (TSAD) seems to be one of the hottest topics in NeurIPS, SIGKDD, VLDB etc.\n\nMany (perhaps most) papers evaluate on Paparrizos’ *TSB-AD-M benchmark…*\n\nHowever, I tested these benchmark datasets and found that in most cases I could beat the SOTA TSAD methods with a 100-year-old algorithm, simple Statistical Process Control (SPC). In the attached example, SPC gets *perfect* results.\n\nIf we can beat the SOTA papers with 100-year-old algorithm, we probably should not be too impressed with them \\[b\\]. I really think this calls for some introspection by the community.\n\nTo be clear, I make no claims (here) about the proposed algorithms in all these paper. But the TSB-AD benchmark is obviously too trivial to make meaningful claims on \\[a\\]\\[b\\].\n\nThe example shown is one of the ECG traces but look at dozen of traces marked “TAO”, they are even more trivial to solve with SPC \\[a\\]\\[c\\].\n\nI do not claim to have solved the triviality problem, but I have done 90% of the work to introduce more challenging TSAD problems (\\[d\\] sled dogs, \\[e\\] Tuna, Fuel Cells, Smart Manufacturing  etc.).\n\n \n\n**TLDR:** I think the TSAD community needs more introspection on benchmarks. Most progress over the last decade seems to be illusionary.  \n\n \n\n\\[a\\] [https://www.youtube.com/watch?v=VftCMSI3C\\_s](https://www.youtube.com/watch?v=VftCMSI3C_s)\n\n\\[b\\] [https://www.dropbox.com/scl/fi/31zuyhejb6sdjrom20frn/Problems-with-Time-Series-Anomaly-Detection.pptx?rlkey=mvcj1wz5s45kgazezopnih2h7&dl=0](https://www.dropbox.com/scl/fi/31zuyhejb6sdjrom20frn/Problems-with-Time-Series-Anomaly-Detection.pptx?rlkey=mvcj1wz5s45kgazezopnih2h7&dl=0)\n\n\\[c\\] [https://www.dropbox.com/scl/fi/42fkf9q9hft2224dnm83v/The-TSB-AD-Benchmarks-are-Nonsense.pptx?rlkey=5fwjopie5ncjhkgr0wqhdm2lp&dl=0](https://www.dropbox.com/scl/fi/42fkf9q9hft2224dnm83v/The-TSB-AD-Benchmarks-are-Nonsense.pptx?rlkey=5fwjopie5ncjhkgr0wqhdm2lp&dl=0)\n\n\\[d\\] [https://www.linkedin.com/feed/update/urn:li:activity:7488825356494237696/](https://www.linkedin.com/feed/update/urn:li:activity:7488825356494237696/)\n\n\\[e\\] [https://www.dropbox.com/scl/fi/hettphvtpyrksggfect9d/Tutorial-on-Pan-Matrix-Profile.pptx?rlkey=p59gd2w56fxl9kl2fh5q819oo&dl=0](https://www.dropbox.com/scl/fi/hettphvtpyrksggfect9d/Tutorial-on-Pan-Matrix-Profile.pptx?rlkey=p59gd2w56fxl9kl2fh5q819oo&dl=0)\n\n\n\n--- Top Comments ---\n\n\n[84 upvotes] Love seeing someone actually check the benchmarks instead of just chasing the leaderboard. The fact that SPC cleans up on these datasets is pretty damning, especially when you look at how many papers treat TSB-AD like the gold standard. Makes you wonder how much of the last few years of TSAD research is just overfitting to toy problems.\n\n[66 upvotes] I was reading this and I was like oh man this is the kind of thing Eamonn Keogh has been trying to get people to pay attention to. Then I saw who posted it ;)\n\n[41 upvotes] [Not a very new claim](https://arxiv.org/abs/2009.13807)\n\nEdit: LOL, just saw the username. Thanks for not letting the claim get stale!\n\n[18 upvotes] I love seeing you put the fear of God into TSAD people on LinkedIn, it's highly amusing. That said, what ARE the good benchmarks? I'm not in that field at all, just curious ",
  "transcript_chars": 3442,
  "ingested_at": "2026-08-30T01:30:07.404468+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 211,
    "upvote_ratio": 1.0,
    "num_comments": 18,
    "author": "eamonnkeogh",
    "is_self": true
  }
}