In choonghyunryu/alookr: Model Classifier for Binary Classification

knitr::opts_chunk$set(collapse = TRUE, comment = "")

Preface

If you created a data set to develop a classification model, you must perform a cleansing of the data. After you create the data set, you should do the following:

• Cleansing the data set
  • Optional removal of variables, including missing values
  • Remove a variable with one unique number
  • Remove categorical variables with a large number of levels
  • Convert a character variable to a categorical variable
• Split the data into a train set and a test set
• Modeling and Evaluate, Predict

The alookr package makes these steps fast and easy:

How to perform cleansing the data set

Refer to the following website for information on how to perform cleansing the data set.

• Cleansing the data set

choonghyunryu/alookr documentation built on Feb. 28, 2024, 3:04 a.m.