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Credit Card Fraud Detection Techniques - Overview

Overview of Credit Card Fraud Detection Techniques

This workflow shows an overview of credit card fraud detection techniques. The performances of the techniques are evaluated on the same test set, and reported in terms of Recall and Precision.

URL: Four Techniques for Outlier Detection https://www.knime.com/blog/four-techniques-for-outlier-detection
URL: Fraud Detection using Random Forest, Neural Autoencoder, and Isolation Forest Techniques https://www.knime.com/blog/fraud-detection-using-random-forest
URL: Credit Card Fraud Detection on Kaggle https://www.kaggle.com/mlg-ulb/creditcardfraud
URL: Overview of Credit Card Fraud Detection Techniques https://youtu.be/-S5f87k8LXI

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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: 2020-09-01
On NodePit since: 2025-01-17
Last update: 2025-01-20
Created with KNIME version: v5.4.0
Tags: credit cardfraudDBSCANbox plotz-scoreoutlierisolation forestautoencoderlogistic regressionrandom forestFinancial services and banking

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