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: 0.3.4
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, party, purrr, ROCR, ranger, rlang, rpart, stats, tibble, tidyr, tidyselect, unbalanced, xgboost
Suggests: knitr, ISLR, mice, mlbench
Published: 2021-02-22
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu at gmail.com>
BugReports: https://github.com/choonghyunryu/alookr/issues
License: GPL-2 | file LICENSE
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: alookr results

Documentation:

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

Downloads:

Package source: alookr_0.3.4.tar.gz
Windows binaries: r-devel: alookr_0.3.4.zip, r-release: alookr_0.3.4.zip, r-oldrel: alookr_0.3.4.zip
macOS binaries: r-release (arm64): alookr_0.3.4.tgz, r-release (x86_64): alookr_0.3.4.tgz, r-oldrel: alookr_0.3.4.tgz
Old sources: alookr archive

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