Package: pomodoro 3.8.0

pomodoro: Predictive Power of Linear and Tree Modeling

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.

Authors:Seyma Kalay <[email protected]>

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pomodoro.pdf |pomodoro.html✨
pomodoro/json (API)

# Install 'pomodoro' in R:

install.packages('pomodoro', repos = c('https://seymakalay.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/seymakalay/pomodoro/issues

Datasets:

sample_data - Sample data for analysis. A dataset containing information of access to credit.

On CRAN:

7 exports 0.63 score 77 dependencies 4 scripts 249 downloads

Last updated 2 years agofrom:337b764fb3. Checks:OK: 3 NOTE: 4. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Aug 22 2024
R-4.5-win	NOTE	Aug 22 2024
R-4.5-linux	NOTE	Aug 22 2024
R-4.4-win	NOTE	Aug 22 2024
R-4.4-mac	NOTE	Aug 22 2024
R-4.3-win	OK	Aug 22 2024
R-4.3-mac	OK	Aug 22 2024

Exports:BAG_Model Combined_Performance Estimate_Models GBM_Model GLM_Model MLM_Model RF_Model

Dependencies:caret class cli clock codetools colorspace cpp11 data.table diagram digest dplyr e1071 fansi farver foreach future future.apply gbm generics ggplot2 globals glue gower gtable hardhat ipred isoband iterators KernSmooth labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix mgcv ModelMetrics munsell nlme nnet numDeriv parallelly pillar pkgconfig plyr pROC prodlim progressr proxy purrr R6 randomForest RColorBrewer Rcpp recipes reshape2 rlang rpart scales shape SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr

Pomodoro_Vignette

Seyma Kalay

Rendered fromPomodoro_Vignette.Rmdusingknitr::rmarkdownon Aug 22 2024.

Last update: 2022-03-29
Started: 2021-10-25

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Bagging Model	BAG_Model
Combined Performance of the Data Splits	Combined_Performance
Results of the Each Data and Data Splits	Estimate_Models
Gradient Boosting Model	GBM_Model
Generalized Linear Model	GLM_Model
Multinominal Logistic Model	MLM_Model
Random Forest	RF_Model
Sample data for analysis. A dataset containing information of access to credit.	sample_data