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Found 6 papers, 1 papers with code
Target alignment in truncated kernel ridge regression
We show that for polynomial alignment, there is an \emph{over-aligned} regime, in which TKRR can achieve a faster rate than what is achievable by full KRR.
A Framework for an Assessment of the Kernel-target Alignment in Tree Ensemble Kernel Learning
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 tree ensembles (particularly in higher dimensional scenarios).
BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values
There has been increasing interest in modeling survival data using deep learning methods in medical research.
(Decision and regression) tree ensemble based kernels for regression and classification
We elucidate the performance and properties of the RF and GBT based kernels in a comprehensive simulation study comprising of continuous and binary targets.
Random Forest (RF) Kernel for Regression, Classification and Survival
We elucidate the performance and properties of the data driven RF kernels used by regularized linear models in a comprehensive simulation study comprising of continuous, binary and survival targets.
DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values
There has been increasing interest in modelling survival data using deep learning methods in medical research.
