Surprise Data
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Surprise Data has 2 facts recorded in Dontopedia across 1 reference.
Maturity scale
raw canonical shape-checked rule-derived certifiedMethodmethod
- Build Full Trainset[1]sourceall time · 51af00c3 127f 47f4 8b3a D5d09a4ce3ae
Rdf:typerdf:type
- Data Source[1]sourceall time · 51af00c3 127f 47f4 8b3a D5d09a4ce3ae
Inbound mentions (1)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
isCreatedFromIs Created From(1)
- Trainset
ex:trainset
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (1)
- custom
ctx:claims/beam/51af00c3-127f-47f4-8b3a-d5d09a4ce3ae- full textbeam-chunktext/plain1 KB
doc:beam/51af00c3-127f-47f4-8b3a-d5d09a4ce3aeShow excerpt
# Use SVD for matrix factorization algo = SVD() trainset = surprise_data.build_full_trainset() algo.fit(trainset) predictions = [] for interaction in interactions: pred = algo.predict(interaction['user_id'], …
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.