Workflow Automation Templates
A library of ready-to-use workflow templates to accelerate your data journey
Model Prediction
Load & apply trained models
Overview
This workflow uses a trained Gradient Boosted Tree (GBT) Regressor model to predict house prices based on input features. It loads the pre-trained model, applies it to a test dataset, evaluates performance, and saves the prediction results.
Details
The process begins with loading the Dataset and preparing the features using the Vector Assembler node. The Spark ML Model Load node retrieves the pre-trained GBT model, which is then used by the Spark Predict node to generate predictions.
Predicted results are previewed using Print N Rows, evaluated for accuracy with the Regression Evaluator, and refined with Select Columns before being saved via the Save CSV node.
This workflow enables efficient deployment, evaluation, and visualization of machine learning predictions in Spark ML environments.