f1_score
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
f1_score has 12 facts recorded in Dontopedia across 3 references, with 4 live disagreements.
Mostly:takes argument(2), rdf:type(2), has parameter(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (2)
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.
callsCalls(1)
- Compute Metrics
ex:compute-metrics
hasComponentHas Component(1)
- Scikit Learn
ex:scikit-learn
Other facts (11)
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 |
|---|---|---|
| Takes Argument | Ground Truth Arg | [1] |
| Takes Argument | Results Arg | [1] |
| Rdf:type | Function | [2] |
| Rdf:type | Function | [3] |
| Has Parameter | Relevant Binary | [2] |
| Has Parameter | Retrieved Binary | [2] |
| Part of | Metric Functions | [2] |
| Part of | Scikit Learn | [3] |
| Is Called | true | [2] |
| Calculates | F1 Metric | [2] |
| Function of | Scikit Learn | [3] |
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 (3)
ctx:claims/beam/059dfa3d-8d94-4bfc-bbe2-1c2228c8c6fe- full textbeam-chunktext/plain1 KB
doc:beam/059dfa3d-8d94-4bfc-bbe2-1c2228c8c6feShow excerpt
total_duration += timer.duration total_throughput += num_queries / timer.duration latencies.append(timer.duration) # Assuming results is a binary array indicating relevance precision = precision_scor…
ctx:claims/beam/dfbb9e1e-3e56-4d8e-b41d-1a690438b469ctx:claims/beam/fe5b22b9-de5a-42a8-ae33-5d8f47d014d6- full textbeam-chunktext/plain1 KB
doc:beam/fe5b22b9-de5a-42a8-ae33-5d8f47d014d6Show excerpt
- The `compute_metrics` function computes accuracy and F1-score using Scikit-learn's `accuracy_score` and `f1_score`. 2. **Collect Data**: - We use `make_classification` to generate synthetic data for demonstration purposes. In a rea…
See also
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