Specify the validation method for Fit Binary Logistic Model

Stat > Regression > Binary Logistic Regression > Fit Binary Logistic Model > Validation

Choose whether to use a test data set to validate your model.


The analysis does not validate the model.

Validation with a test set

Complete the following steps to divide the data into a training data set and a test data set.

  1. From the drop-down list, select Validation with a test set.
  2. Choose one of the following to specify whether to select a fraction of rows randomly or with an ID column.
    • Randomly select a fraction of rows as a test set: Select this option to have Minitab randomly select the test data set. You can specify how much data to use in the test data set. The default value of 0.3 works well in most cases. You want to include enough data in the test data set to evaluate the model well. If you are unsure about the form of the model, a larger test data set provides stronger validation. You also want enough data in the training data set to estimate the model well. Typically, models with more predictors require more training data to estimate.
    • Define training/test split by ID column: Select this option to select the rows to include in the test sample yourself. In ID column, enter the column that indicates which rows to use for the test sample. The ID column must contain only 2 values. In Level for test set, select which level to use as the test sample.
  3. (Optional) Check Store ID column for training/test split to save the ID column.
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