Nithish2410/recommendations-ml-100k

MovieLens Leave-One-Out Five chronological interactions predict the next interaction. One final test target per user; no rating filter. Histories are audit-only, not wholesale model inputs. Actors are supplementary; see actor_sources.json. { "schema": "movie-fields-v1", "source": "official MovieLens 100K", "sample_policy": "leave-one-out-windows", "past_order": "oldest-first", "history_length": 5, "stride": 1, "shuffle_seed": 42, "timestamp_policy": "rating… See the full description on the dataset page: https://huggingface.co/datasets/Nithish2410/recommendations-ml-100k.

<iframe src="https://silytics.si/embed/item/13e7d972-6349-45b2-8c42-2b29bdc71754" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.