DATASET_NORMALIZE_WORKERS

DATASET_NORMALIZE_FIT Worker

Overview

A new worker, DATASET_NORMALIZE_FIT, has been added to Workflows.

This worker standardizes numeric dataset columns using available (non-missing) values and generates the normalization parameters required for consistent data preprocessing. The resulting parameters can be used by downstream normalization and inverse-normalization workflows.

Key Features

  • Added support for the DATASET_NORMALIZE_FIT worker in Workflows
  • Standardizes numeric dataset columns using non-missing values
  • Computes and stores normalization parameters
  • Supports consistent dataset preprocessing across workflows
  • Integrates with normalization and inverse-normalization processes


DATASET_NORMALIZE_APPLY Worker

Overview

A new worker, DATASET_NORMALIZE_APPLY, is now available in Workflows.

This worker standardizes numeric dataset columns using normalization parameters generated by the DATASET_NORMALIZE_FIT worker. By applying previously calculated mean and standard deviation values, the worker ensures consistent normalization across datasets without recalculating the normalization parameters.

Key Features

  • Added support for the DATASET_NORMALIZE_APPLY worker in Workflows
  • Standardizes numeric dataset columns using precomputed normalization parameters
  • Uses mean and standard deviation values generated by DATASET_NORMALIZE_FIT
  • Ensures consistent normalization across multiple datasets
  • Supports machine learning and analytics preprocessing workflows


DATASET_NORMALIZE_INVERSE Worker

Overview

A new worker, DATASET_NORMALIZE_INVERSE, is now available in Workflows.

This worker reverses a previously applied normalization transformation, restoring normalized numeric dataset columns back to their original scale using the normalization parameters generated by the DATASET_NORMALIZE_FIT worker.

The worker is particularly useful for converting model outputs, predictions, or transformed datasets back into their original units for interpretation, reporting, and downstream processing.

Key Features

  • Added support for the DATASET_NORMALIZE_INVERSE worker in Workflows
  • Restores normalized numeric columns to their original scale
  • Uses normalization parameters generated by DATASET_NORMALIZE_FIT
  • Supports inverse transformation without recalculating parameters
  • Integrates seamlessly with normalization workflows