"train_predict_mix" predicts the binary response with binary features

c(
person(given = "Mohsen",
family = "Sadatsafavi",
role = c("aut", "cph"),
email = "msafavi@mail.ubc.ca",
comment = c(ORCID = "0000-0002-0419-7862")),
person("Amin", "Adibi", email = "adibi@alumni.ubc.ca", role = c("cre"),
comment = c(ORCID = "0000-0003-2748-4781")),
person("Abdollah", "Safari", email = "asafari@mail.ubc.ca", role = c("aut"))
)
Provides additional functions for evaluating predictive models, including plotting calibration curves and model-based Receiver Operating Characteristic (mROC) based on Sadatsafavi et al (2021) <arXiv:2003.00316>.
Rcpp, pROC, stats, graphics, RConics, ggplot2, dplyr, magrittr
Mohsen Sadatsafavi [aut, cph] (<https://orcid.org/0000-0002-0419-7862>),
Amin Adibi [cre] (<https://orcid.org/0000-0003-2748-4781>),
Abdollah Safari [aut]

Makes the time series prediction easier by automatizing this process
using four main functions: prep(), modl(), pred() and postp(). Features different
preprocessing methods to homogenize variance and to remove trend and seasonality.
Also has the potential to bring together different predictive models to make comparatives.
Features ARIMA and Data Mining Regression models (using caret).
caret, forecast, graphics, methods, Metrics, stats, TSPred,
tseries, utils
2017-09-19 16:00:57 UTC; Alberto Vico Moreno

c(person("Alberto", "Vico Moreno", role=c("aut","cre"),email="avm00016@red.ujaen.es"),
person("Antonio Jesus","Rivera Rivas",role=c("aut","ths"),email="arivera@ujaen.es"),
person("Maria Dolores","Perez Godoy",role=c("aut","ths"),email="lperez@ujaen.es"))
Alberto Vico Moreno [aut, cre],
Antonio Jesus Rivera Rivas [aut, ths],
Maria Dolores Perez Godoy [aut, ths]
2018-04-29 13:45:20 UTC; Alberto Vico Moreno

R Package for Pairwise Preference Elicitation
Allows users to derive multi-objective weights from pairwise comparisons, which
research shows is more repeatable, transparent, and intuitive other techniques. These weights
can be rank existing alternatives or to define a multi-objective utility function for optimization.