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Self-supervised Stacking Ensemble

Self-supervised Stacking Ensemble combines stacked generalization — the classic two-level ensemble architecture introduced by Wolpert (1992) — with self-supervised pretraining, allowing base models to learn rich representations from unlabeled data before being fine-tuned and stacked. This hybrid strategy is especially powerful when labeled examples are scarce but unlabeled data is plentiful.

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Self-supervised Stacking Ensemble (SSL-augmented Stacked Generalization)

Rekod kaedah taksonomik · ml-model / machine-learning

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