Normalization

This operator performs normalization on the selected columns of the input data set. Normalization means adjusting values measured on different scales to a notionally common scale.

Normalization operator icon

Information at a Glance

Note: This operator can only be used with TIBCO® Data Virtualization and Apache Spark 3.2 or later.

Parameter

 Description
Category Transform
Data source type TIBCO® Data Virtualization
Send output to other operators Yes
Data processing tool TIBCO® DV, Apache Spark 3.2 or later

Algorithm

You can accomplish normalization in the following ways:

  • By specifying a user-defined minimum and maximum value.
  • By a z-transformation (for example, on mean 0 and variance 1).
  • By a transformation as a proportion of the average or sum of the respective attribute.

Your selection translates into four possible types of normalization:

  • Z-Transformation.
  • Proportion Transformation.
  • Range Transformation.
  • Divide-By-Average Transformation.

Input

An input is a single tabular data set.

Bad or Missing Values
Null values are not allowed and result in an error.

Configuration

The following table provides the configuration details for the Normalization operator.

Parameter Description
Notes Notes or helpful information about this operator's parameter settings. When you enter content in the Notes field, a yellow asterisk appears on the operator.
Method Specify the normalization method to use. The following values are available:

  • Divide-By-Average Transformation: Calculate by the sample's average.
  • Proportional Transformation: Calculate by sample's sum.
  • Z-Transformation: Calculate by sample's mean and variance.
  • Range Transformation: Calculate by sample's minimum and maximum value.

Range Minimum Specify the minimum value in Range transformation.
Range Maximum Specify the maximum value in Range transformation.
Columns Specify the columns to normalize by selecting the available numerical columns. Click Column Names to open the dialog for selecting the available numerical columns.
Output Schema Specify the schema for the output table or view.
Output Table Specify the table path and name where the output of the results is generated. By default, this is a unique table name based on your user ID, workflow ID, and operator.
Store Results When set to Yes, the operator saves the results. If set to No, the operator does not save the results.

Output

Visual Output
  • Output: A table that displays the output of a data set for the normalized data.

Example

The following example displays the normalized data for the given data set using the Normalization operator.

Normalization operator workflow
Data
golf: This data set contains the following information:
  • Multiple columns namely outlook, temperature, wind, humidity, and play.
  • Multiple rows (14 rows).
Parameter Setting
The parameter settings for the golf data set are as follows:

  • Method: Proportional Transformation

  • Columns: outlook, humidity, wind, play, temperature

  • Store Results: Yes

Output
The following figure displays the output for the parameter settings for the golf data set.
Normalization operator output tab