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pomodoro  

Predictive Power of Linear and Tree Modeling
View on CRAN: Click here


Download and install pomodoro package within the R console
Install from CRAN:
install.packages("pomodoro")

Install from Github:
library("remotes")
install_github("cran/pomodoro")

Install by package version:
library("remotes")
install_version("pomodoro", "3.8.0")



Attach the package and use:
library("pomodoro")
Maintained by
Seyma Kalay
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-01-10
Latest Update: 2022-03-26
Description:
Runs generalized and multinominal logistic (GLM and MLM) models, as well as random forest (RF), Bagging (BAG), and Boosting (BOOST). This package prints out to predictive outcomes easy for the selected data and data splits.
How to cite:
Seyma Kalay (2022). pomodoro: Predictive Power of Linear and Tree Modeling. R package version 3.8.0, https://cran.r-project.org/web/packages/pomodoro. Accessed 22 Dec. 2024.
Previous versions and publish date:
3.3.0 (2022-01-10 09:32)
Other packages that cited pomodoro R package
View pomodoro citation profile
Other R packages that pomodoro depends, imports, suggests or enhances
Complete documentation for pomodoro
Functions, R codes and Examples using the pomodoro R package
Some associated functions: BAG_Model . Combined_Performance . Estimate_Models . GBM_Model . GLM_Model . MLM_Model . RF_Model . sample_data . 
Some associated R codes: BAG_Model.R . Combined_Performance.R . Estimate_Models.R . GBM_Model.R . GLM_Model.R . MLM_Model.R . RF_Model.R . sample_data.R .  Full pomodoro package functions and examples
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