A toolbox for designing and evaluating predictive models with resampling methods. The aim of this package is to provide a simple and efficient general framework for working with any type of prediction problem, be it classification, regression or survival analysis, that is easy to extend and adapt to your specific setting. Some commonly used methods for classification, regression and survival analysis are included.
factor_to_logical) and a pre-processing wrapper for it
(pre_factor_to_logical).select
function (#2). The initial purpose of having dplyr as a dependency rather
than an import was to automatically attach it upon loading emil to allow
class-specific extension to select. The current solution provides the same
functionality without affecting the global search path.