GradientBoostingClassifier
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
GradientBoostingClassifier has 11 facts recorded in Dontopedia across 1 reference, with 3 live disagreements.
Mostly:has parameter n estimators(3), has parameter learning rate(3), has parameter max depth(3)
Maturity scale
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containsContains(1)
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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.
| Predicate | Value | Ref |
|---|---|---|
| Has Parameter N Estimators | 50 | [1] |
| Has Parameter N Estimators | 100 | [1] |
| Has Parameter N Estimators | 200 | [1] |
| Has Parameter Learning Rate | 0.01 | [1] |
| Has Parameter Learning Rate | 0.1 | [1] |
| Has Parameter Learning Rate | 1 | [1] |
| Has Parameter Max Depth | 3 | [1] |
| Has Parameter Max Depth | 4 | [1] |
| Has Parameter Max Depth | 5 | [1] |
| Rdf:type | Gradient Boosting Classifier | [1] |
Timeline
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References (1)
ctx:claims/beam/0daa7c15-b2c7-44ef-a5e9-390bf6864c0a- full textbeam-chunktext/plain1 KB
doc:beam/0daa7c15-b2c7-44ef-a5e9-390bf6864c0aShow excerpt
df = pd.read_csv('data.csv') # Split the data into training and testing sets X_train, X_test, y_train, y_test = train_test_split(df['text'], df['label'], test_size=0.2, random_state=_42) # Feature extraction vectorizer = TfidfVectorizer()…
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