Fraud Detection: Random Forest Model Deployment
We read the trained model, as well as the new transaction and applies the model to classify it. We use a Rule Engine node to apply a threshold. In case a transaction is classified as fraudulent the workflow sends an email to notify of a fraud.
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
Workflow
02_Deployment Random Forest for Fraud Detection
Used extensions & nodes
Created with KNIME Analytics Platform version 5.2.5
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