Icon

CI_​IA_​Payroll_​Social_​Security_​Error_​Detection

Keras Autoencoder for Fraud Detection Training

The aim of the flow is to detect anomalies in social security contributions. It is based on the autoencoder principle.

Data Preprocessing Training the Autoencoder Model evaluation Data Preprocessing Deploying the Autoencoder Reporting Training Deploying Apply networkApply network Keras NetworkLearner Keras NetworkExecutor Excel Reader Scorer Excel Reader Keras NetworkExecutor Excel Writer Data Preprocessing Keras AutoencoderArchitecture Data Prprocessing Class calculation Class calculation Data Preprocessing Training the Autoencoder Model evaluation Data Preprocessing Deploying the Autoencoder Reporting Training Deploying Apply networkApply network Keras NetworkLearner Keras NetworkExecutor Excel Reader Scorer Excel Reader Keras NetworkExecutor Excel Writer Data Preprocessing Keras AutoencoderArchitecture Data Prprocessing Class calculation Class calculation

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: 2023-08-27
Last update: 2024-11-21
Created with KNIME version: v4.7.2
Tags: autoencoderKerasneural networkbackpropagationdeep learningencoderdecoderreconstructionfraud detectionanomaly detectionmodel trainingmodel evaluationfraudcybersecurityinternal controlpayrollsocial security contributions

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

Try NodePit Runner!