A minimum divergence method for model weighting in prediction averaging shows small-sample advantages over stacking and Akaike-style weighting.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Divergence-Based Method for Weighting and Averaging Model Predictions
A minimum divergence method for model weighting in prediction averaging shows small-sample advantages over stacking and Akaike-style weighting.