CARRoT: R-package for predictive modelling by means of regression, adjusted for multiple regularisation methods.

ABSTRACT: We present an R-package for predictive modelling, CARRoT (Cross-validation, Accuracy, Regression, Rule of Ten). CARRoT is a tool for initial exploratory analysis of the data, which performs exhaustive search for a regression model yielding the best predictive power with heuristic 'rules of thumb' and expert knowledge as regularization parameters. It uses multiple hold-outs in order to internally validate the model. The package allows to take into account multiple factors such as collinearity of the predictors, event per variable rules (EPVs) and R-squared statistics during the model selection. In addition, other constraints, such as forcing specific terms and restricting complexity of the predictive models can be used. The package allows taking pairwise and three-way interactions between v

SUBMITTER: Bazarova A 

PROVIDER: S-EPMC10569555 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature