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Introduce alookr

Choonghyun Ryu

2024-02-11

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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