Machine Learning Fraud Detection Pipeline

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This workflow streamlines fraud detection by integrating data importation, preprocessing, and sophisticated feature engineering with machine learning. It focuses on analyzing transaction data, highlighting anomalies, and calculating key metrics for fraud risk assessment. Emphasizing customer behavior and terminal risk over varied time frames, it leads to the development of an accurate, reusable machine learning model. This No-Code/Low-Code pipeline adeptly navigates the intricacies of large-scale fraud analysis.

URL: Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook https://fraud-detection-handbook.github.io/fraud-detection-handbook/Foreword.html

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• FeatureKNIME Base nodes
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