Lightgbm Model
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Lightgbm Model has 11 facts recorded in Dontopedia across 1 reference, with 3 live disagreements.
Mostly:parameter n estimators(3), parameter learning rate values(3), parameter max depth values(3)
Maturity scale
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Other facts (11)
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| Predicate | Value | Ref |
|---|---|---|
| Parameter N Estimators | 50 | [1] |
| Parameter N Estimators | 100 | [1] |
| Parameter N Estimators | 200 | [1] |
| Parameter Learning Rate Values | 0.01 | [1] |
| Parameter Learning Rate Values | 0.1 | [1] |
| Parameter Learning Rate Values | 1 | [1] |
| Parameter Max Depth Values | 3 | [1] |
| Parameter Max Depth Values | 4 | [1] |
| Parameter Max Depth Values | 5 | [1] |
| Rdf:type | Classification Model | [1] |
| Class Name | LGBMClassifier | [1] |
Timeline
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References (1)
ctx:claims/beam/b3aa5dac-a3f5-477c-922c-cef12e6cc5a9- full textbeam-chunktext/plain1 KB
doc:beam/b3aa5dac-a3f5-477c-922c-cef12e6cc5a9Show excerpt
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() X_train_tfidf = vectorizer.fit_transform(X_train) X_test_tfidf = vectorizer.tr…
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