Bank Loan Modeling with Auto Categorical Features Embedding

This workflow demonstrates use of Auto Categorical Features Embedding node. It is a Bank Loan data where likelihood of default is to be predicted. The dataset has 18 categorical features. These features get transformed to numeric features using the three transformation methods available in the node. Results are comparable with and without feature transformation--feature transformed data having a minor edge.

External resources

• Bank Loan Default Modeling--Kaggle