Dontopedia

Tracking Metrics Code

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

Tracking Metrics Code has 10 facts recorded in Dontopedia across 1 reference.

10 facts·10 predicates·1 sources

Mostly:rdf:type(1), has function(1), appends to f1 scores(1)

Maturity scale raw canonical shape-checked rule-derived certified

Other facts (10)

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.

10 facts
PredicateValueRef
Rdf:typePython Script[1]
Has FunctionTrack Metrics[1]
Appends to F1 ScoresF1[1]
Logs Iteration InfoLogging[1]
Calculates Average AccuracyAvg Accuracy[1]
Calculates Average F1Avg F1[1]
Logs Average MetricsLogging[1]
Invokes Track MetricsTrack Metrics[1]
Imports NumpyNumpy[1]
Imports LoggingLogging[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.

typebeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:PythonScript
hasFunctionbeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:track_metrics
appendsToF1Scoresbeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:f1
logsIterationInfobeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:logging
calculatesAverageAccuracybeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:avg_accuracy
calculatesAverageF1beam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:avg_f1
logsAverageMetricsbeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:logging
invokesTrackMetricsbeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:track_metrics
importsNumpybeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:numpy
importsLoggingbeam/4d8a9041-50ce-43e0-932c-4a659a199f0e
ex:logging

References (1)

1 references
  1. ctx:claims/beam/4d8a9041-50ce-43e0-932c-4a659a199f0e
    • full textbeam-chunk
      text/plain1 KBdoc:beam/4d8a9041-50ce-43e0-932c-4a659a199f0e
      Show excerpt
      f1_scores.append(f1) logging.info(f"Iteration {i+1}: Accuracy={accuracy:.4f}%, F1-Score={f1:.4f}") avg_accuracy = np.mean(accuracies) avg_f1 = np.mean(f1_scores) logging.info(f"Average Accuracy: {avg_accurac

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