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fraud-detection's Introduction

CSE-573-SWM-Fraud-Detection

Fraud Detection With Graph Databases and Machine Learning

Data

This project consists of the following datasets:

  • BankSim Dataset: bs140513_032310.csv
  • Graph-Based Data: graph_features_dataset.csv

Code

Python Scripts

  • graph_featuresset.py: Generates graph features from Neo4j and exports to graph_features_dataset.csv.
  • graphdb_creation.cyp: Contains commands for pushing data into the Neo4j tool.
  • graphplot.py: Plots the graph using Matplotlib in Python.
  • graphfeatures.py: Generates graph features using Python.

Features Extracted

The following features are extracted:

  • merchDegree
  • custDegree
  • merchCloseness
  • custCloseness
  • custPageRank
  • merchPageRank
  • custBetweeness
  • merchBetweeness
  • merchlouvain
  • custlouvain
  • merchCommunity
  • custCommunity

Web Files

  • index.html: HTML file for data visualization.
  • main.js: JavaScript code for data visualization.

fraud-detection's People

Contributors

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Watchers

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