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]>

pomodoro_3.8.0.tar.gz
pomodoro_3.8.0.zip(r-4.7-any)pomodoro_3.8.0.zip(r-4.6-any)pomodoro_3.8.0.zip(r-4.5-any)
pomodoro_3.8.0.tgz(r-4.6-any)pomodoro_3.8.0.tgz(r-4.5-any)
pomodoro_3.8.0.tar.gz(r-4.7-any)pomodoro_3.8.0.tar.gz(r-4.6-any)
pomodoro_3.8.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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

Pkgdown/docs site:https://seymakalay.github.io

Datasets:

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

On CRAN:

3.70 score 5 scripts 255 downloads 7 exports 75 dependencies

Last updated from:337b764fb3. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel	NOTE	139
source / vignettes	OK	278
linux-release	NOTE	157
macos-release	NOTE	177
macos-oldrel	NOTE	172
windows-devel	NOTE	116
windows-release	NOTE	121
windows-oldrel	NOTE	107
wasm-release	OK	108

Exports:BAG_Model Combined_Performance Estimate_Models GBM_Model GLM_Model MLM_Model RF_Model

Dependencies:caret class cli clock codetools cpp11 data.table diagram digest dplyr e1071 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 ModelMetrics nlme nnet numDeriv parallelly pillar pkgconfig plyr pROC prodlim progressr proxy purrr R6 randomForest RColorBrewer Rcpp recipes reshape2 rlang rpart S7 scales shape sparsevctrs SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr

Pomodoro_Vignette

Estimate_Models | Combined_Performance

Rendered fromPomodoro_Vignette.Rmdusingknitr::rmarkdown

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