Other packages > Find by keyword >

CARRoT  

Predicting Categorical and Continuous Outcomes Using One in Ten Rule
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]
All associated links for this package
First Published: 2018-04-06
Latest Update: 2023-10-13
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. Accessed 26 Aug. 2026.
Previous versions and publish date:
0.1.0 (2018-04-06 12:52), 1.0.0 (2018-06-30 19:04), 1.5.0 (2018-11-27 23:30), 2.0.0 (2019-03-07 22:53), 2.5.0 (2020-03-26 11:10), 2.5.1 (2020-05-14 00:00), 2.5.2 (2021-06-08 12:10), 3.0.0 (2023-04-17 23:50), 3.0.1 (2023-08-15 14:20), (2026-07-09 07:59)
Other packages that cited CARRoT R package
View CARRoT citation profile
Other R packages that CARRoT depends, imports, suggests or enhances
Complete documentation for CARRoT
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
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

leafgl  
High-Performance 'WebGl' Rendering for Package 'leaflet'
Provides bindings to the 'Leaflet.glify' JavaScript library which extends the 'leaflet' JavaScript l ...
Download / Learn more Package Citations See dependency  
PCADSC  
Tools for Principal Component Analysis-Based Data Structure Comparisons
A suite of non-parametric, visual tools for assessing differences in data structures for two datase ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
clinUtils  
General Utility Functions for Analysis of Clinical Data
Utility functions to facilitate the import, the reporting and analysis of clinical data. Example ...
Download / Learn more Package Citations See dependency  
SelvarMix  
Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis
Performs a regularization approach to variable selection in themodel-based clustering and classifica ...
Download / Learn more Package Citations See dependency  
ncodeR  
Techniques for Automated Classifiers
A set of techniques that can be used to develop, validate, and implement automated classifiers. A po ...
Download / Learn more Package Citations See dependency  

28,332

R Packages

239,283

Dependencies

75,113

Author Associations

28,333

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA