In choonghyunryu/alookr: Model Classifier for Binary Classification

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

Preface

The original data must be divided into train and test data sets to develop a classification model. You should do the following:

• Cleansing the data set
• 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 data set
    • Comparison of categorical variables
    • Comparison of numeric variables
    • Diagnosis of train set and test set
  • Extract train/test data set
    • 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

Refer to the following website for information on splitting the data into a train and test set.

• Splitting the dataset

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