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Undersample

Abstract

To address the imbalance in data labels, reduce majority classes to minority classes.

To address the imbalance in data labels, reduce majority classes to minority classes.

Tip

You can only use it if you have a sufficient amount of data. Undersampling small data sets can cause you to lose useful data.

When to use this tool

Use to address classification problems in your data.

Configuration

Use the following configuration options to help configure the Undersample tool.

Configuring the Undersample tool

  1. In Varicent ELT, go to the Pipes module.

  2. On the Pipes tab, find the pipe you want to work with. Click the pipe to open.

  3. In your Pipe builder add your data source.

  4. On the canvas toolbar, click symon_add_icon.png + Tool.

  5. In the Tools modal search bar, type Undersample.

    Tip

    You can also find the Undersample tool in the Data section.

  6. Click + Add Tool.

  7. Connect the tool to your data set.

  8. In the configuration pane, enter the following information:

    Table 61. Undersample tool configuration

    Field

    Description

    Target column

    Select the target column to use as an undersample of data.