Splitting the dataset

In alookr: Model Classifier for Binary Classification

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

Preface

To develop a classification model, the original data must be divided into train data set and test data set. You should do the following:

• Cleansing the dataset
• Split the data into a train set and a test set
  • Split the data.frame or tbl_df into a train set and a test set
  • Compare dataset
    • Comparison of categorical variables
    • Comparison of numeric variables
    • Diagnosis of train set and test set
  • Extract train/test dataset
    • Extract train set or test set
    • Extract the data to fit the model
• Modeling and Evaluate, Predict

The alookr package makes these steps fast and easy:

How to perform split the data

For information on how to perform split the data into a train set and a test set, refer to the following website.

• Splitting the dataset

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