Workflow Automation Templates
A library of ready-to-use workflow templates to accelerate your data journey
Data Normalization
Standardize features to unit norm
Overview
This workflow normalizes feature vectors to a unit norm, ensuring that all input variables contribute equally to model training. Normalization improves learning stability, model accuracy, and convergence speed for algorithms sensitive to feature scaling.
Details
The workflow begins by loading the housing dataset. The Vector Assembler node combines all input features into a single vector suitable for processing. The Normalizer node then scales each feature vector to have a unit norm, standardizing feature ranges across the dataset.
The normalized data is displayed using the Print N Rows node for inspection. This process enhances model performance by reducing bias caused by differing feature magnitudes and ensures consistency across datasets.