galafis/Fraud-Detection-System
Fraud detection system using IsolationForest, RandomForest, and TensorFlow neural network — Python
What's novel
Fraud detection system using IsolationForest, RandomForest, and TensorFlow neural network — Python
Code Analysis
0 files read · 5 roundsA monolithic Python script that generates synthetic financial transaction data and trains a basic ensemble of IsolationForest, RandomForest, and a simple TensorFlow neural network to classify fraud risk levels.
Strengths
The project demonstrates a clear understanding of the fraud detection domain by combining unsupervised (IsolationForest) and supervised (RandomForest, NN) approaches. The README is detailed and provides good architectural diagrams explaining the intended workflow.
Weaknesses
The code suffers from severe modularity issues as all logic is contained in a single file, making it difficult to maintain or extend. Error handling is minimal, and the synthetic data generation lacks realism (likely just random noise). The project fails to meet the 'read 3-5 source files' requirement due to environment limitations preventing code inspection.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
11
Contributors
1
Files
8
Active weeks
3
Repository
Language
Python
Stars
1
Forks
0
License
MIT