Kernel density estimation applied to bagged neural network predictions yields a representative output and confidence score that outperforms mean or median aggregation in nonlinear regression.
A comprehensive evaluation of ensemble m achine learning in geotechnical stability analysis and explainability
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
Evaluation of Bagging Predictors with Kernel Density Estimation and Bagging Score
Kernel density estimation applied to bagged neural network predictions yields a representative output and confidence score that outperforms mean or median aggregation in nonlinear regression.