ROSE - Random Over-Sampling Examples
Functions to deal with binary classification problems in the presence of imbalanced classes. Synthetic balanced samples are generated according to ROSE (Menardi and Torelli, 2013). Functions that implement more traditional remedies to the class imbalance are also provided, as well as different metrics to evaluate a learner accuracy. These are estimated by holdout, bootstrap or cross-validation methods.
Last updated 3 years ago
6.74 score 4 stars 2 packages 1.5k scripts 16k downloadsBCgee - Bias-Corrected Estimates for Generalized Linear Models for Dependent Data
Provides bias-corrected estimates for the regression coefficients of a marginal model estimated with generalized estimating equations. Details about the bias formula used are in Lunardon, N., Scharfstein, D. (2017) <doi:10.1002/sim.7366>.
Last updated 1 years ago
1.00 score 4 scripts 238 downloads