We propose recursively imputed survival tree (RIST) regression for right-censored data. This new nonparametric regression procedure uses a novel recursive imputation approach combined with extremely randomized trees that allows significantly better use of censored data than previous tree-based...

Diagnostic checking for multivariate parametric models is investigated in this article. A nonparametric Monte Carlo Test (NMCT) procedure is proposed. This Monte Carlo approximation is easy to implement and can automatically make any test procedure scale-invariant even when the test statistic is...

This article introduces a new machine learning task, called latent supervised learning, where the goal is to learn a binary classifier from <italic>continuous</italic> training labels that serve as surrogates for the unobserved class labels. We investigate a specific model where the surrogate variable arises...