This Node Is Deprecated — This node is kept for backwards-compatibility, but the usage in new workflows is no longer recommended. The documentation below might contain more information.

This node normalizes the values of all (numeric) columns. In the dialog, you can choose the columns you want to work on. The following normalization methods are available in the dialog:


Min-max normalization
Linear transformation of all values such that the minimum and maximum in each column are as given.
Z-score normalization
Linear transformation such that the values in each column are Gaussian-(0,1)-distributed, i.e. mean is 0.0 and standard deviation is 1.0.
Normalization by decimal scaling
The maximum value in a column (both positive and negative) is divided j-times by 10 until its absolute value is smaller or equal to 1. All values in the column are then divided by 10 to the power of j.

Input Ports

Table requiring normalization of some or all columns.

Output Ports

Table with normalized columns.
Model containing normalization parameters, which can be used in a "normalize apply" node to normalize test data the same way as the training data has been normalized.


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