YZ Sözlüğü

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Functional Gradient Descent

Optimization technique that adjusts model parameters in the direction opposite to the gradient of the loss function in function space.

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Gradient Boosting Machines (GBM)

Class of algorithms implementing the gradient boosting method with various loss functions and weak learners.

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Bagging vs Boosting

Fundamental distinction where bagging trains models independently in parallel while boosting builds them sequentially by correcting errors.

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Loss function gradient

Partial derivative of the loss function with respect to predictions, indicating the direction of greatest possible improvement.

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Regularization in GBM

Set of techniques (L1/L2, tree constraints, shrinkage) controlling model complexity to prevent overfitting.

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Newton's method in GBM

Variant of gradient boosting using the Hessian matrix (second derivative) for more optimal parameter updates.