# Calculate the recall score
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
# Calculate the recall score has 5 facts recorded in Dontopedia across 1 reference.
Mostly:rdf:type(1), describes(1), precedes(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedOther facts (4)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Code Comment | [1] |
| Describes | Recall Calculation | [1] |
| Precedes | Recall Calculation | [1] |
| Comment Type | instructional | [1] |
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)
ctx:claims/beam/b3bf4b36-b6fb-4f89-a967-2ebf362c0106- full textbeam-chunktext/plain1 KB
doc:beam/b3bf4b36-b6fb-4f89-a967-2ebf362c0106Show excerpt
# Train the model model = SparseModel() model.fit(train_df) # Make predictions predictions = model.predict(test_df) # Calculate the recall score recall = recall_score(test_df['label'], predictions) print(f'Recall score: {recall:.3f}') ```…
See also
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