n_estimators
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
n_estimators has 4 facts recorded in Dontopedia across 2 references, with 1 live disagreement.
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (3)
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.
hasParameterHas Parameter(2)
- Gradient Boosting Classifier
ex:gradient-boosting-classifier - Random Forest Classifier
ex:RandomForestClassifier
instantiatedWithInstantiated With(1)
- Random Forest Classifier
ex:random-forest-classifier
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.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Model Parameter | [1] |
| Rdf:type | Tree Count | [2] |
| Parameter Value | 100 | [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.
References (2)
ctx:claims/beam/b1f15a8f-0818-47c8-9428-a2f1b0f3d957- full textbeam-chunktext/plain1 KB
doc:beam/b1f15a8f-0818-47c8-9428-a2f1b0f3d957Show excerpt
# Test the model y_pred = model.predict(X_test_scaled) accuracy = accuracy_score(y_test, y_pred) logger.info(f"Test Accuracy: {accuracy:.2f}") return model, accuracy # Example data features = np.random.rand(18000, …
ctx:claims/beam/5cde1b20-a0d7-44d7-bf40-d61f95aa4245- full textbeam-chunktext/plain1 KB
doc:beam/5cde1b20-a0d7-44d7-bf40-d61f95aa4245Show excerpt
logging.basicConfig(filename='evaluation_pipeline.log', level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s') # Load dataset X, y = np.random.rand(10000, 10), np.random.randint(0, 2, 10000) # Split t…
See also
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