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stat.ML2021
A Framework for an Assessment of the Kernel-target Alignment in Tree Ensemble Kernel Learning
Dai Feng, Richard Baumgartner
Kernels ensuing from tree ensembles such as random forest (RF) or gradient boosted trees (GBT), when used for kernel learning, have been shown to be competitive to their respective…
stat.ML2020★ 1 cited
(Decision and regression) tree ensemble based kernels for regression and classification
Dai Feng, Richard Baumgartner
Tree based ensembles such as Breiman's random forest (RF) and Gradient Boosted Trees (GBT) can be interpreted as implicit kernel generators, where the ensuing proximity matrix repr…
stat.ML2020★ 1 cited
Random Forest (RF) Kernel for Regression, Classification and Survival
Dai Feng, Richard Baumgartner
Breiman's random forest (RF) can be interpreted as an implicit kernel generator,where the ensuing proximity matrix represents the data-driven RF kernel. Kernel perspective on the R…