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Quantitative Finance · Glossário

O que é Early stopping?

Definition 5.6 Machine Learning for Markets · Capítulo 5 — Trees and Boosting

Early stopping stops an iterative fit (more trees, more epochs) at the iteration where the loss on a validation block, purged from the training rows, is lowest.

Validation R-squared (40 purged months) of boosted trees as trees are added, at two learning rates; dashed, the early-stopping points (34 and 233 trees). The curve at = 0.1 leaves the frame after about 340 trees and reaches -2.9\% at 600. Data: ml_trees.early.
Figure 5.2. Validation R-squared (40 purged months) of boosted trees as trees are added, at two learning rates; dashed, the early-stopping points (34 and 233 trees). The curve at η=0.1\eta = 0.1 leaves the frame after about 340 trees and reaches −2.9%-2.9\% at 600. Data: ml_trees.early.
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