Dontopedia

Sklearn Random Forest

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Sklearn Random Forest has 2 facts recorded in Dontopedia across 2 references.

2 facts·2 predicates·2 sources
Maturity scale raw canonical shape-checked rule-derived certified

Other facts (2)

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2 facts
PredicateValueRef
Subclass ofDecision Tree Ensemble[1]
Rdf:typeEnsemble Method[2]

Timeline

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2 undated
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subclassOfbeam/9fbd5d54-37d5-44fc-b34f-86313fb7e94a
ex:decision-tree-ensemble
—
typebeam/5679be66-975d-4ac3-8008-e70820051098
ex:EnsembleMethod

References (2)

2 references
  1. [1]9fbd5d54 37d5 44fc B34f 86313fb7e94a1 fact
    ctx:claims/beam/9fbd5d54-37d5-44fc-b34f-86313fb7e94a
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9fbd5d54-37d5-44fc-b34f-86313fb7e94a
      Show excerpt
      logging.info(f"Iteration {iteration}: Model accuracy = {accuracy:.4f}") # Example usage: model = RandomForestClassifier(n_estimators=100) for i in range(5): # Example: Fine-tune and evaluate the model 5 times fine_tuned_model = fi…
  2. [2]5679be66 975d 4ac3 8008 E708200510981 fact
    ctx:claims/beam/5679be66-975d-4ac3-8008-e70820051098
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5679be66-975d-4ac3-8008-e70820051098
      Show excerpt
      from sklearn.model_selection import train_test_split from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score, classification_report, confusion_matrix import logging # Set up logging configuration logg…

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