Boosting Classifiers with Tightened L0-Relaxation Penalties (ICML 2010) Noam Goldberg, Jonathan Eckstein [Paper] Boosting for Regression Transfer (ICML 2010) David Pardoe, Peter Stone [Paper] [Code] Boosted Backpropagation Learning for Training Deep Modular Networks (ICML 2010) Alexander Grubb, J....
即Bagging方法Combine the prediction of different hypothesis by some sort of voting是一种分类器结合的方法1.1 源起1.1.2 BootstrapBagging方法是Bootstrap思想的一种应用Bootstrap EstimationRepeatedly draw n samples from DFor each set of samples, estimate a statisticThe bootstrap estimate is the mean of ...
In this framework, the pseudo-label and importance of an unlabeled sample are estimated based on the additive logistic regression for an integration of a prior model and an online classifier learned on one feature view, and then used to update the weak classifiers built on the other feature ...
where no distributional assumption on the effect sizes is made. Although limited from the computational perspective due to the extremely high-dimensional data in GWAS, high-dimensional linear regression is a natural model for GWAS in modelling the whole-genome level contributions of genetic variation...