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01_​Autoencoder_​for_​Fraud_​Detection_​Training

Keras Autoencoder for Fraud Detection - Training

This workflow trains an autoendcoder model to detect fraudulent transactions.



Keras Autoencoder Architecture Data Preprocessing Training the Autoencoder Optimizing threshold K Final Performance Read credit card dataTop:Class = 02/3 of negativesfor training1/3 of negativesand all positivesfor validationMin-max normalizationClassifytransactions based onthreshold10 % for validationWrite modelNormalizerfor deployment Classthreshold.tableShape: 30Units: 40Activation: SigmoidUnits: 20Activation: SigmoidUnits: 8Activation: SigmoidUnits: 20Activation: SigmoidUnits: 40Activation: SigmoidUnits: 30Activation: SigmoidTrain with Loss function=MSEOptimizer=AdamApply networkFile Reader Row Splitter Partitioning Concatenate Normalizer Rule Engine Normalizer (Apply) Partitioning Keras NetworkWriter Scorer (JavaScript) Model Writer Normalizer (Apply) ThresholdOptimization Math Formula Number To String Table Writer Variable toTable Row Keras Input Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras NetworkLearner Keras NetworkExecutor Keras Autoencoder Architecture Data Preprocessing Training the Autoencoder Optimizing threshold K Final Performance Read credit card dataTop:Class = 02/3 of negativesfor training1/3 of negativesand all positivesfor validationMin-max normalizationClassifytransactions based onthreshold10 % for validationWrite modelNormalizerfor deployment Classthreshold.tableShape: 30Units: 40Activation: SigmoidUnits: 20Activation: SigmoidUnits: 8Activation: SigmoidUnits: 20Activation: SigmoidUnits: 40Activation: SigmoidUnits: 30Activation: SigmoidTrain with Loss function=MSEOptimizer=AdamApply networkFile Reader Row Splitter Partitioning Concatenate Normalizer Rule Engine Normalizer (Apply) Partitioning Keras NetworkWriter Scorer (JavaScript) Model Writer Normalizer (Apply) ThresholdOptimization Math Formula Number To String Table Writer Variable toTable Row Keras Input Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras Dense Layer Keras NetworkLearner Keras NetworkExecutor

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Created by: Maarit Laukkanen
Created at: 2019-02-25
On NodePit since: 2020-12-17
Last update: 2024-04-16
Created with KNIME version: v4.2.3
Tags: autoencoderKerasneural networkdeep learningencoderdecoderreconstructioncredit card datafraud detectionanomaly detectionmodel evaluationbankingcredit cardfraudcybersecurity

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