ec4e6c0d96 | ||
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.gitignore | ||
Binary_SOM.R | ||
Categorical_SOM.R | ||
Clusters.R | ||
Clusters_2.R | ||
Data_Prep.R | ||
Detecting_Bitcoin_Ransomware.R | ||
Detecting_Bitcoin_Ransomware.Rmd | ||
Detecting_Bitcoin_Ransomware.pdf | ||
Final_method.R | ||
Heirarchical_Clustering.R | ||
Heirarchical_K-Means_Clustering.R | ||
K-Means_Clustering.R | ||
LICENSE | ||
Predictions.R | ||
README.md | ||
RanFor.R | ||
Ransomware-Bitcoin-Addresses.R | ||
Ransomware-Bitcoin-Addresses.Rmd | ||
SOM_test.R | ||
Visuals.R |
README.md
Ransomware Detection on the Bitcoin Blockchain
using Random Forests and Self Organizing Maps
Final submission form CYO project at HarvardX PH125.9x Capstone Course
Machine learning project on BitcoinHeist data set.
https://archive.ics.uci.edu/ml/datasets/BitcoinHeistRansomwareAddressDataset
Most of these files are exploratory scripts that helped to develop the final script.
The main three files that can be considered the final project are:
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Detecting_Bitcoin_Ransomware.pdf (Final report)
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Detecting_Bitcoin_Ransomware.Rmd (R markdown that generates the report)
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Detecting_Bitcoin_Ransomware.R (R script that contains the essential code for the modeling process)
Everything else can be safely ignored, and is just here so that I can trace my own steps if needed.