A bootstrap procedure estimates the quantile of the regression ensemble convergence gap mse_t minus mse_infinity, with a non-asymptotic guarantee for the ideal functional and good empirical performance.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ML 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting
A bootstrap procedure estimates the quantile of the regression ensemble convergence gap mse_t minus mse_infinity, with a non-asymptotic guarantee for the ideal functional and good empirical performance.