Dontopedia

weighted average

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

weighted average has 9 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

9 facts·4 predicates·3 sources·2 in dispute

Mostly:rdf:type(3), used by(2), is parameter for(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (4)

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.

calculatesCalculates(1)

calculationTypeCalculation Type(1)

methodMethod(1)

supportsAveragingMethodSupports Averaging Method(1)

Other facts (7)

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.

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/ebda2d07-c933-44d1-ba4e-dbff565d177a
ex: AveragingMethod
isParameterForbeam/ebda2d07-c933-44d1-ba4e-dbff565d177a
ex:f1_score
typebeam/6624bde3-d339-4d6d-b7d6-d46af0d14d82
ex:MathematicalOperation
labelbeam/6624bde3-d339-4d6d-b7d6-d46af0d14d82
weighted average
usesInputbeam/6624bde3-d339-4d6d-b7d6-d46af0d14d82
ex:feedback-factors
usedBybeam/6624bde3-d339-4d6d-b7d6-d46af0d14d82
ex:calculate-refined-projection
typebeam/d375d85b-650d-469e-9f0b-11950f22f89a
ex:AggregationMethod
labelbeam/d375d85b-650d-469e-9f0b-11950f22f89a
weighted average
usedBybeam/d375d85b-650d-469e-9f0b-11950f22f89a
ex:f1-score

References (3)

3 references
  1. ctx:claims/beam/ebda2d07-c933-44d1-ba4e-dbff565d177a
    • full textbeam-chunk
      text/plain995 Bdoc:beam/ebda2d07-c933-44d1-ba4e-dbff565d177a
      Show excerpt
      ### Example Code for Classification Task Here's an example of how you might evaluate a classification task using accuracy and F1 score in Python: ```python from sklearn.metrics import accuracy_score, f1_score, confusion_matrix # Predicti
  2. ctx:claims/beam/6624bde3-d339-4d6d-b7d6-d46af0d14d82
  3. ctx:claims/beam/d375d85b-650d-469e-9f0b-11950f22f89a

See also

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