Cleansing the dataset

In alookr: Model Classifier for Binary Classification

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

Preface

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

• Cleansing the dataset
  • 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 dataset

For information on how to perform cleansing the dataset, refer to the following website.

• Cleansing the dataset

alookr documentation built on June 12, 2022, 5:08 p.m.