Dontopedia

update_weights

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

update_weights has 20 facts recorded in Dontopedia across 3 references, with 6 live disagreements.

20 facts·10 predicates·3 sources·6 in dispute

Mostly:has parameter(4), rdf:type(3), returns(2)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (8)

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usedInUsed in(2)

containsContains(1)

containsComponentContains Component(1)

demonstratesFunctionDemonstrates Function(1)

hasFunctionHas Function(1)

mentionsMentions(1)

resultOfResult of(1)

Other facts (18)

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.

18 facts
PredicateValueRef
Has ParameterEngine1 Accuracy Parameter[2]
Has ParameterEngine2 Accuracy Parameter[2]
Has ParameterEngine1 Accuracy[3]
Has ParameterEngine2 Accuracy[3]
Rdf:typeFunction[1]
Rdf:typeFunction[2]
Rdf:typeFunction[3]
ReturnsTuple of Weights[2]
ReturnsNew Weights[3]
Contains LogicTotal Accuracy Calculation[2]
Contains LogicNew Weights Calculation[2]
ImplementsWeight Optimization[2]
ImplementsWeight Adjustment Process[2]
Is Part ofExample Code[1]
Is Definedfalse[1]
Is Incompletetrue[1]
Is Not Implementedtrue[1]
Has Conditional BranchZero Accuracy Check[2]

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.

typebeam/cfaeceec-0bb8-418e-b19c-694784b98555
ex:Function
labelbeam/cfaeceec-0bb8-418e-b19c-694784b98555
update weights based on performance metrics
isPartOfbeam/cfaeceec-0bb8-418e-b19c-694784b98555
ex:example-code
isDefinedbeam/cfaeceec-0bb8-418e-b19c-694784b98555
false
isIncompletebeam/cfaeceec-0bb8-418e-b19c-694784b98555
true
isNotImplementedbeam/cfaeceec-0bb8-418e-b19c-694784b98555
true
typebeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:Function
labelbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
update_weights
hasParameterbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:engine1-accuracy-parameter
hasParameterbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:engine2-accuracy-parameter
returnsbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:tuple-of-weights
containsLogicbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:total-accuracy-calculation
hasConditionalBranchbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:zero-accuracy-check
containsLogicbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:new-weights-calculation
implementsbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:weight-optimization
implementsbeam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
ex:weight-adjustment-process
typebeam/12bcf927-76eb-4b53-96b5-c31748201d41
ex:Function
hasParameterbeam/12bcf927-76eb-4b53-96b5-c31748201d41
ex:engine1-accuracy
hasParameterbeam/12bcf927-76eb-4b53-96b5-c31748201d41
ex:engine2-accuracy
returnsbeam/12bcf927-76eb-4b53-96b5-c31748201d41
ex:new-weights

References (3)

3 references
  1. ctx:claims/beam/cfaeceec-0bb8-418e-b19c-694784b98555
    • full textbeam-chunk
      text/plain1 KBdoc:beam/cfaeceec-0bb8-418e-b19c-694784b98555
      Show excerpt
      Let's assume you have two retrieval engines, `engine1` and `engine2`, and you want to dynamically adjust their weights based on their performance metrics. #### Step 1: Collect Performance Metrics You can collect performance metrics by com
  2. ctx:claims/beam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
    • full textbeam-chunk
      text/plain1 KBdoc:beam/34ffcd35-801a-4acf-b1f5-659bb6c98a27
      Show excerpt
      def update_weights(engine1_accuracy, engine2_accuracy): total_accuracy = engine1_accuracy + engine2_accuracy if total_accuracy == 0: return (0.5, 0.5) # Default equal weights if both accuracies are zero new_weights = (e
  3. ctx:claims/beam/12bcf927-76eb-4b53-96b5-c31748201d41
    • full textbeam-chunk
      text/plain1 KBdoc:beam/12bcf927-76eb-4b53-96b5-c31748201d41
      Show excerpt
      new_weights = update_weights(engine1_accuracy, engine2_accuracy) print("Updated Weights:", new_weights) # Recompute ensemble scores with updated weights ensemble_scores = compute_weighted_ensemble_scores(scores1, scores2, weights=new_weigh

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