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