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Cross Entropy

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

Cross Entropy has 4 facts recorded in Dontopedia across 1 reference, with 1 live disagreement.

4 facts·3 predicates·1 sources·1 in dispute
Maturity scale raw canonical shape-checked rule-derived certified

Takes Inputin disputetakesInput

  • Labels Tensor[1]sourceall time · 7ac5933b 630f 4153 B2c5 26299e74cbac
  • Outputs[1]sourceall time · 7ac5933b 630f 4153 B2c5 26299e74cbac

Rdfs:labelrdfs:label

  • cross_entropy[1]sourceall time · 7ac5933b 630f 4153 B2c5 26299e74cbac

Rdf:typerdf:type

Inbound mentions (1)

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.

computedUsingComputed Using(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.

labelbeam/7ac5933b-630f-4153-b2c5-26299e74cbac
cross_entropy
typebeam/7ac5933b-630f-4153-b2c5-26299e74cbac
ex:lossFunction
takesInputbeam/7ac5933b-630f-4153-b2c5-26299e74cbac
ex:labels_tensor
takesInputbeam/7ac5933b-630f-4153-b2c5-26299e74cbac
ex:outputs

References (1)

1 references
  1. [1]beam-chunk4 facts
    customctx:claims/beam/7ac5933b-630f-4153-b2c5-26299e74cbac
    • full textbeam-chunk
      text/plain1 KBdoc:beam/7ac5933b-630f-4153-b2c5-26299e74cbac
      Show excerpt
      # Example processing (replace with actual model training code) inputs_tensor = torch.tensor(inputs, dtype=torch.float32) labels_tensor = torch.tensor(labels, dtype=torch.long) outputs = model(inputs_tensor)

See also

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