Normalization

Normalization consists of transforming numeric values into a specific range, such as [–1.0,1.0] or [0.0,1.0] such that x_new = (x_old-shift)/scale. Normalization applies only to numeric attributes.

Oracle Data Miner enables you to specify the following kinds of normalization:

• Min Max: Normalizes each attribute using the transformation x_new = (x_old-min)/(max-min)

• Linear Scale: Normalizes each attribute using the transformation x_new = (x_old-shift)/scale

• Z-Score: Normalizes numeric attributes using the mean and standard deviation computed from the data. Normalizes each attribute using the transformation
x_new = (x-mean)/standard deviation

• Custom: The user defines normalization.

Normalization provides transformations that perform min-max normalization, scale normalization, and z-score normalization.