Dontopedia

Parameter Space

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

Parameter Space has 3 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

3 facts·2 predicates·2 sources·1 in dispute
Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (5)

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.

exploresExplores(4)

rdf:typeRdf:type(1)

Other facts (3)

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.

3 facts
PredicateValueRef
Explored byGrid Search[1]
Explored byRandom Search[1]
Explored byGrid Search Cv[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.

exploredBybeam/cc7e2701-5558-4a53-b31f-07382bf903bd
ex:grid-search
exploredBybeam/cc7e2701-5558-4a53-b31f-07382bf903bd
ex:random-search
explored-bybeam/7835e578-f2e3-46a0-aa40-4497812bf8de
ex:grid-search-cv

References (2)

2 references
  1. ctx:claims/beam/cc7e2701-5558-4a53-b31f-07382bf903bd
    • full textbeam-chunk
      text/plain1 KBdoc:beam/cc7e2701-5558-4a53-b31f-07382bf903bd
      Show excerpt
      dense_scores = np.array([0.7, 0.3, 0.1]) # Normalize and compute hybrid scores hybrid_scores = hybrid_ranking(sparse_scores, dense_scores) print(hybrid_scores) # Optionally, sort documents based on hybrid scores sorted_indices = np.argsor
  2. ctx:claims/beam/7835e578-f2e3-46a0-aa40-4497812bf8de
    • full textbeam-chunk
      text/plain1 KBdoc:beam/7835e578-f2e3-46a0-aa40-4497812bf8de
      Show excerpt
      recall = recall_score(y_test, predictions) print(f'{name} Recall score: {recall:.3f}') print(classification_report(y_test, predictions)) print(confusion_matrix(y_test, predictions)) print('-' * 50) ``` ### Explanat

See also

Keep researching

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