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gptkbp:instanceOf
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Machine Learning Algorithm
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gptkbp:application
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gptkb:insurance
Finance
Marketing
Fraud Detection
Image Classification
Ranking
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gptkbp:basedOn
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Ensemble Learning
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gptkbp:consistsOf
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Multiple Decision Trees
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gptkbp:contrastsWith
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gptkb:Bagging
gptkb:Random_Forests
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gptkbp:feature
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Combining Weak Learners
Sequential Training
Weighted Data Points
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https://www.w3.org/2000/01/rdf-schema#label
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Boosted Trees
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gptkbp:hyperparameter
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Learning Rate
Minimum Child Weight
Number of Trees
Subsample Ratio
Tree Depth
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gptkbp:implementedIn
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gptkb:Spark_MLlib
gptkb:scikit-learn
R
CatBoost Library
LightGBM Library
XGBoost Library
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gptkbp:improves
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Prediction Accuracy
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gptkbp:introducedIn
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gptkb:Robert_Schapire
gptkb:Yoav_Freund
1990s
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gptkbp:limitation
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Overfitting
Computational Cost
Sensitivity to Noisy Data
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gptkbp:reduces
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Variance
Bias
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gptkbp:relatedTo
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gptkb:Bagging
gptkb:Random_Forests
Decision Trees
Stacking
Ensemble Methods
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gptkbp:supportsAlgorithm
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gptkb:CatBoost
gptkb:LightGBM
gptkb:XGBoost
gptkb:Gradient_Boosting
gptkb:AdaBoost
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gptkbp:usedIn
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Regression
Classification
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gptkbp:bfsParent
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gptkb:Classification_and_Regression_Tree
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gptkbp:bfsLayer
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7
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