Hands-On Deep Learning with R

Train and test data

When we build predictive models, we need to create two separate sets of data with the help of the following segments. One is used by the model to learn the task and the other is used to test how well the model learned the task. Here are the types of data that we will look at:

• Train data: The segment of the data used to fit the model. The model has access to the explainer variables or independent variables, which are the selected columns, to describe a record in your data, as well as the target variable or dependent variable. That is the value we are trying to predict during the training process using this dataset. This segment should usually be between 50% and 80% of your total data.
• Test data: The segment of the data ...