In this section, we will prepare the data for building the classification model. Data preparation will involve normalizing the data, partitioning the data into training and test data, and carrying out one-hot encoding of the response variable.
Preparing the data for model building
Normalizing numeric variables
For developing deep network models, we carry out the normalization of numeric variables to bring them to a common scale. When dealing with several variables, it is likely that different variables have different scales—for example, there could be a variable that shows revenues earned by a company and the values could be in millions of dollars. In another example, there could be a variable that shows the dimension...