Apache® Spark™ News

Using AutoML Toolkit’s FamilyRunner Pipeline APIs to Simplify and Automate Loan Default Predictions

In the post Using AutoML Toolkit to Automate Loan Default Predictions, we had shown how the Databricks Labs’ AutoML Toolkit simplified Machine Learning model feature engineering and model building optimization (MBO).  It also had improved the area-under-the-curve (AUC) from 0.6732 (handmade XGBoost model) to 0.723 (AutoML XGBoost model).  With AutoML Toolkit’s Release 0.6.1, we have upgraded to MLflow version 1.3.0 and introduced a new Pipeline API that simplifies feature generation and inference.