alookr: Model Classifier for Binary Classification

A collection of tools that support data splitting, predictive modeling, and model evaluation. A typical function is to split a dataset into a training dataset and a test dataset. Then compare the data distribution of the two datasets. Another feature is to support the development of predictive models and to compare the performance of several predictive models, helping to select the best model.

Version:	0.3.9
Depends:	R (≥ 3.2.0), ggplot2 (≥ 3.0.0), randomForest
Imports:	caTools, cli (≥ 1.1.0), dlookr, dplyr (≥ 0.7.6), future, ggmosaic, MASS, MLmetrics, methods, parallelly, party, purrr, ROCR, ranger, rlang, rpart, stats, tibble, tidyr, tidyselect, xgboost, glmnet
Suggests:	knitr, ISLR, mice, mlbench, rmarkdown, stringi
Published:	2024-02-11
Author:	Choonghyun Ryu [aut, cre]
Maintainer:	Choonghyun Ryu <choonghyun.ryu at gmail.com>
BugReports:	https://github.com/choonghyunryu/alookr/issues
License:	GPL-2
NeedsCompilation:	no
Language:	en-US
Materials:	NEWS
CRAN checks:	alookr results

Documentation:

Reference manual:	alookr.pdf
Vignettes:	Cleansing the dataset Introduce alookr Classification Modeling Splitting the dataset

Downloads:

Package source:	alookr_0.3.9.tar.gz
Windows binaries:	r-devel: alookr_0.3.9.zip, r-release: alookr_0.3.9.zip, r-oldrel: alookr_0.3.9.zip
macOS binaries:	r-release (arm64): alookr_0.3.9.tgz, r-oldrel (arm64): alookr_0.3.9.tgz, r-release (x86_64): alookr_0.3.9.tgz, r-oldrel (x86_64): alookr_0.3.9.tgz
Old sources:	alookr archive

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