Overview
Syllabus
Introduction
KNIME Analytics Platform
KNIME nodes & workflow
Goals for the Session
Fraud is all around us
Potentially fraudulent data
Fraudulent data might be labelled
Decision Tree
Random Forest
Advanced: Sampling Strategies
Finding fraud through deep learning
A neural autoencoder in KNIME
Walk through how to do the same task using unlabeled data Jinwei
Fraud and Outlier Detection
Finding Outliers: Statistics
Demo IQR and Z-score Implementation in KNIME
DBSCAN
Summary
Useful Fraud-related links
Useful KNIME-related links
Q&A
Taught by
Data Science Dojo