Webinar: Approaches to Fraud Detection: Autoencoder, Isolation Forest and More - February 22, 2023

Join @victor_palacios and @jinweisun on February 22 at 12 PM - 1PM (PST) / 9 PM - 10 PM UTC+1 (Berlin)

In the first part of this webinar, we will work with labelled data to perform classical machine-learning approaches to fraud detection such as the random forest. Then we will cover a deep learning technique, the autoencoder, to find fraudulent data points.

In the second part of the webinar, we will focus on data without labels of fraudulent activity using visualisations, classical statistics, and machine learning. You will learn how easy it is to generate multiple visualisations, perform statistical analysis, and use two machine learning algorithms – Isolation Forest and DBSCAN – all to detect fraudulent activity in the free, open-source KNIME Analytics Platform.

In this session you will learn:

  • How to identify fraud using a variety of techniques including visualisations, statistics, and machine learning.
  • How to use machine learning and deep learning algorithms for fraud detection regardless of whether you have labelled data or not.

Register for the webinar Here



Hi Everyone, we had some questions from the webinar, so I’ll put relevant links here:

  1. Dealing with imbalanced data: Sampling Strategies Comparison – KNIME Community Hub

  2. Rule Engine for multiple sources/rules and column expression: Possibility to combine multiple Rule engine nodes (like Math multi-column function)

  3. Cybersecurity Fraud: Cyber security – KNIME Community Hub

  4. Healthcare Fraud: (I’m linking PDF analysis for fraud here as most of healthcare deals with scraping pdfs for information) Outlier Dection / Fraud Detection in Contracts – KNIME Community Hub

  5. Time Series Sampling: Time Series Analysis with Components | KNIME

  6. KNIME Model Object: PMML Integration in KNIME | KNIME

  7. SMOTE: [1106.1813] SMOTE: Synthetic Minority Over-sampling Technique

  8. Getting conda for free to use in KNIME: Anaconda | Anaconda Distribution

1 Like

This topic was automatically closed 90 days after the last reply. New replies are no longer allowed.