best_weights
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
best_weights has 20 facts recorded in Dontopedia across 5 references, with 4 live disagreements.
Mostly:rdf:type(5), is result of(2), updated when(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (9)
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.
assignsAssigns(1)
- Best Weights Assignment
ex:best_weights-assignment
consumesConsumes(1)
- Fusion
ex:fusion
displaysDisplays(1)
- Print Statement
ex:print-statement
formatsVariableFormats Variable(1)
- Best Weights Print
ex:best-weights-print
printsPrints(1)
- Print Statement
ex:print-statement
returnsReturns(1)
- Tune Weights
ex:tune_weights
takesArgumentsTakes Arguments(1)
- Fuse Scores
ex:fuse_scores
trackedByTracked by(1)
- Best Solution
ex:best_solution
usesUses(1)
- Fusion
ex:fusion
Other facts (17)
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 | Variable | [1] |
| Rdf:type | Variable | [2] |
| Rdf:type | Variable | [3] |
| Rdf:type | Dictionary | [4] |
| Rdf:type | Configuration | [5] |
| Is Result of | Tune Weights | [1] |
| Is Result of | Optimization Process | [5] |
| Updated When | best_precision_condition | [4] |
| Updated When | best_precision_updated | [4] |
| Is | Variable | [1] |
| Assigned by | Tune Weights | [1] |
| Output of | Tune Weights | [1] |
| Represents | Best Weights Combination | [3] |
| Tracks Corresponding | Best Precision | [4] |
| Is Associated With | Best Precision | [5] |
| Is Normalization of | Normalized Weights | [5] |
| Is Output of | Conditional Assignment | [5] |
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 (5)
ctx:claims/beam/33fac88e-670b-45ad-bc1c-45cb2091b14a- full textbeam-chunktext/plain1002 B
doc:beam/33fac88e-670b-45ad-bc1c-45cb2091b14aShow excerpt
# Example data scores1 = np.array([0.8, 0.2, 0.4]) scores2 = np.array([0.3, 0.7, 0.1]) labels = np.array([1, 0, 1]) # Example labels # Tune weights best_weights = tune_weights(scores1, scores2, labels) print(f"Best weights: {best_weights}…
ctx:claims/beam/876593fe-f346-4056-accb-7ea33bea2791ctx:claims/beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb- full textbeam-chunktext/plain1 KB
doc:beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bbShow excerpt
# Output the best combination of weights print(f"Best Intent Precision: {best_precision}") print(f"Best Weights: {best_weights}") ``` ### Explanation 1. **Define Context Components and Initial Weights**: Identify the components of your co…
ctx:claims/beam/1ffcc69a-673e-4e51-9fb2-8fb50597b6ee- full textbeam-chunktext/plain1 KB
doc:beam/1ffcc69a-673e-4e51-9fb2-8fb50597b6eeShow excerpt
# Check if the reformulated query matches the expected intent if check_intent_match(query, reformulated_query): correct_count += 1 precision = correct_count / len(test_queries) return precision def …
ctx:claims/beam/8c53f93c-330d-4b71-9b2a-a7c521b5200c- full textbeam-chunktext/plain1 KB
doc:beam/8c53f93c-330d-4b71-9b2a-a7c521b5200cShow excerpt
# Evaluate the precision precision = evaluate_intent_precision(normalized_weights, test_queries) # Track the best combination if precision > best_precision: best_precision = precision best_weights = norm…
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