Data Preparation for Neural Network

Neural Network algorithms normalize numeric data, convert categorical data into binary attributes, and handle missing values automatically.

The algorithm automatically "explodes" categorical data into a set of binary attributes, one per category value. Oracle Machine Learning algorithms automatically handle missing values and therefore, missing value treatment is not necessary.

The algorithm automatically replaces missing categorical values with the mode and missing numerical values with the mean. The algorithm requires the normalization of numeric input and it uses z-score normalization. The normalization occurs only for two-dimensional numeric columns (not nested). Normalization places the values of numeric attributes on the same scale and prevents attributes with a large original scale from biasing the solution. Neural Network scales the numeric values in nested columns by the maximum absolute value seen in the corresponding columns.