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CARRoT
View on CRAN: Click
here
Download and install CARRoT package within the R console
Install from CRAN:
install.packages("CARRoT")
Install from Github:
library("remotes")
install_github("cran/CARRoT")
Install by package version:
library("remotes")
install_version("CARRoT", "3.0.2")
Attach the package and use:
library("CARRoT")
Maintained by
Alina Bazarova
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-04-06
Latest Update: 2023-08-15
Description:
Predicts categorical or continuous outcomes while concentrating on a number of key points. These are Cross-validation, Accuracy, Regression and Rule of Ten or "one in ten rule" (CARRoT), and, in addition to it R-squared statistics, prior knowledge on the dataset etc. It performs the cross-validation specified number of times by partitioning the input into training and test set and fitting linear/multinomial/binary regression models to the training set. All regression models satisfying chosen constraints are fitted and the ones with the best predictive power are given as an output. Best predictive power is understood as highest accuracy in case of binary/multinomial outcomes, smallest absolute and relative errors in case of continuous outcomes. For binary case there is also an option of finding a regression model which gives the highest AUROC (Area Under Receiver Operating Curve) value. The option of parallel toolbox is also available. Methods are described in Peduzzi et al. (1996) , Rhemtulla et al. (2012) , Riley et al. (2018) , Riley et al. (2019) .
How to cite:
Alina Bazarova (2018). CARRoT: Predicting Categorical and Continuous Outcomes Using One in Ten Rule. R package version 3.0.2, https://cran.r-project.org/web/packages/CARRoT
Previous versions and publish date:
Other packages that cited CARRoT R package
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Other R packages that CARRoT depends,
imports, suggests or enhances
Functions, R codes and Examples using
the CARRoT R package
Some associated functions: AUC . av_out . comb . compute_max_length . compute_max_weight . compute_weights . cross_val . cub . find_int . find_sub . get_indices . get_predictions . get_predictions_lin . get_probabilities . make_numeric . make_numeric_sets . quadr . regr_ind . regr_whole . sum_weights_sub .
Some associated R codes: carrot_functions.R . Full CARRoT package functions and examples
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