Author: Choonghyun Ryu
Date: 2026-01-11

# Introduce alookr

#### Choonghyun Ryu

#### 2026-01-11

## Overview

Binary classification modeling with `alookr`.

Features:

- Clean and split data sets to train and test.
- Create several representative models.
- Evaluate the performance of the model to select the best model.
- Support the entire process of developing a binary classification model.

The name `alookr` comes from `looking at the analytics process` in the data analysis process.

## Install alookr

The released version is available on CRAN. but not yet.

    install.packages("alookr")

Or you can get the development version without vignettes from GitHub:

    devtools::install_github("choonghyunryu/alookr")

Or you can get the development version with vignettes from GitHub:

    install.packages(c("ISLR", "spelling", "mlbench"))
    devtools::install_github("choonghyunryu/alookr", build_vignettes = TRUE)

## Usage

alookr includes several vignette files, which we use throughout the documentation.

Provided vignettes is as follows.

- Cleansing the dataset
- Split the data into a train set and a test set
- Modeling and Evaluate, Predict

    browseVignettes(package = "alookr")

## How to use dlookr package

For information on how to use dlookr package, refer to the following website.

- `Introduce alookr`