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05_​Isolation_​Forest_​for_​Fraud_​Detection_​Training

Isolation Forest for Fraud Detection: Model Training
Train an isolation forest model for fraud detection using the KNIME H2O Machine Learning Integration 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 dataOpen the viewto see the scoringresultsWrite IsolationForest.model 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 Model Writer Train an isolation forest model for fraud detection using the KNIME H2O Machine Learning Integration 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 dataOpen the viewto see the scoringresultsWrite IsolationForest.modelRow 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 Model Writer

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

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Created by: Maarit Laukkanen
Created at: 2019-02-25
On NodePit since: 2019-07-23
Last update: 2024-04-17
Created with KNIME version: v4.3.0
Tags: fraudh2oisolation forestbankingcredit cardcybersecurity

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