Icon

Isolation_​Forest_​for_​Fraud_​Detection_​Training

Isolation Forest for Fraud DetectionThis workflows uses the Python Integration to implement the Isolation Forest Algorithm to detect fraudulent transactions. Top:Class = 02/3 of negativesfor training1/3 of negativesand all positivesfor validationCreate H2O FrameCreate H2O FrameCreate KNIMETableApply IsolationForest to get Mean Length Classify Based onMean LengthRead credit card data Row Splitter Partitioning Concatenate Table to H2O Table to H2O H2O to Table H2O IsolationForest Learner H2O IsolationForest Predictor Rule Engine File Reader H2O Local Context Component Isolation Forest for Fraud DetectionThis workflows uses the Python Integration to implement the Isolation Forest Algorithm to detect fraudulent transactions. Top:Class = 02/3 of negativesfor training1/3 of negativesand all positivesfor validationCreate H2O FrameCreate H2O FrameCreate KNIMETableApply IsolationForest to get Mean Length Classify Based onMean LengthRead credit card data Row Splitter Partitioning Concatenate Table to H2O Table to H2O H2O to Table H2O IsolationForest Learner H2O IsolationForest Predictor Rule Engine File Reader H2O Local Context Component

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: Maarit Laukkanen
Created at: 2019-02-25
On NodePit since: 2019-10-03
Last update: 2024-04-18
Created with KNIME version: v4.0.0

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!