Fraud Detection: Isolation Forest model deployment
This workflow reads the trained isolation forest model, as well as the incoming transaction and applies the model to it. Based on the isolation number (mean length) and a threshold, the 'Rule Engine' node detects fraudulent transactions and sends an email, if the isolation number is lower than the specified threshold on Mean Length. The isolation forest model is a part of the KNIME H2O Machine Learning Integration.
This workflow demonstrates how we can use the trained Random Forest Model on new data by performing the following steps:
1. Read the model and new data
2. Apply the model on the new transaction
This workflow reads the trained isolation forest model, as well as the incoming transaction and applies the model to it. Based on the isolation number (mean length) and a threshold, the 'Rule Engine' node detects fraudulent transactions and sends an email, if the isolation number is lower than the specified threshold on Mean Length. The isolation forest model is a part of the KNIME H2O Machine Learning Integration.
This workflow demonstrates how we can use the trained Random Forest Model on new data by performing the following steps:
1. Read the model and new data
2. Apply the model on the new transaction