Your Model’s MSE Is Lying to You
Machine LearningYour Model’s MSE Is Lying to YouFirst in a series on probabilistic forecasting for physical signals. The model looks at the recent history, thinks for a moment, and gives you a single number: 0.50.50.5.There's a threshold τ=1.0\tau = 1.0τ=1.0 that fires an alarm. The question is: should you worry?You can't answer that.
- ▪Machine LearningYour Model’s MSE Is Lying to YouFirst in a series on probabilistic forecasting for physical signals.
- ▪The model looks at the recent history, thinks for a moment, and gives you a single number: 0.50.50.5.There's a threshold τ=1.0\tau = 1.0τ=1.0 that fires an alarm.
- ▪The question is: should you worry?You can't answer that.
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| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/your-models-mse-is-lying-to-you/ |
| Publication time | Mon, 14 Sep 2026 19:30:01 GMT |
| Retrieval time | 2026-09-14T19:31:52.711Z |
| Last seen | 2026-09-14T19:31:52.711Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 1DaHvIZpc7S7 · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Machine LearningYour Model’s MSE Is Lying to YouFirst in a series on probabilistic forecasting for physical signals. Next: what happens when you roll the forecast forward more than one step.Waleed EsmailSeptember 14, 202624 min readWhy mean squared error hides the uncertainty in a forecast, and the probabilistic loss that recovers it.Two models, one number, opposite realitiesImagine you have a sensor recording something you care about, for example seismic background at a detector site, electrical load on a grid, or strain in a bridge cable, and you've trained a model to forecast the next value. The model looks at the recent history, thinks for a moment, and gives you a single number: 0.50.50.5.There's a threshold τ=1.0\tau = 1.0τ=1.0 that fires an alarm.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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