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Part A_​Fraud_​Detection_​Model_​Training (2021)

Fraud Detection: Model Training

This workflow reads in the creditcard.csv file and trains and evaluates a Random Forest model to classify transactions as either fraudulent or not. Notice the final Rule Engine node. This node classifies all transactions with fraud probability above 0.3 as fraudulent.

Fraud Detection: Model TrainingThis workflow reads in the creditcard.csv file and trains and evaluates a Random Forest model to classify transactions as eitherfraudulent or not. Notice the final Rule Engine node. This node classifies all transactions with fraud probability above 0.3 as fraudulent. Part A: Model Training Read creditcard.csv70 % Training30 % TestingClass = FraudP(Class =1)>0.3=>1P(Class=1)<= 1Save Model File Reader(deprecated) Partitioning Random ForestLearner Random ForestPredictor Rule Engine Evaluation Model Writer(deprecated) Fraud Detection: Model TrainingThis workflow reads in the creditcard.csv file and trains and evaluates a Random Forest model to classify transactions as eitherfraudulent or not. Notice the final Rule Engine node. This node classifies all transactions with fraud probability above 0.3 as fraudulent. Part A: Model Training Read creditcard.csv70 % Training30 % TestingClass = FraudP(Class =1)>0.3=>1P(Class=1)<= 1Save Model File Reader(deprecated) Partitioning Random ForestLearner Random ForestPredictor Rule Engine Evaluation Model Writer(deprecated)

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: kathrinmelcher
Created at: 2018-06-13
On NodePit since: 2024-11-05
Last update: 2026-01-30
Created with KNIME version: v4.4.1
Tags: fraudfraud detectionrandom forestdeploymentbankingcredit cardcyber security

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