# Introduce alookr

## 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.