Tugas IYKRA Data MBA. Fraud Detection dengan Machine Learning, menggunakan data imbalanced dan dengan jumlah data yang cukup besar, lebih dari 600.000 data.
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Aug 22, 2020 - Jupyter Notebook
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credit-fraud
Here are 7 public repositories matching this topic...
Classification Credit Scoring with Compare Algorithm ML (Ensambled) with Model Evaluation
machine-learning random-forest exploratory-data-analysis feature-selection feature-engineering credit-scoring final-project loan-default-prediction high-accuracy random-forest-classifier credit-fraud
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Aug 25, 2022 - Jupyter Notebook
In this project, I will use credit risk models to assess the credit risk using peer-to-peer lending. Algorithms such as SMOTE, Naive Random Sampling, etc.
peer-to-peer linear-regression time-series-analysis credit-risk smote-sampling credit-fraud naive-random-oversampler smoteenn-combination
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Sep 8, 2021 - Jupyter Notebook
A project of credit fraudulent detection in R using Machine Learning method.
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May 21, 2021 - R
"Data Analytics Challenge" course at the Catholic University of Eichstätt-Ingolstadt
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Apr 17, 2025 - Jupyter Notebook
Synthetic Identity Syndicate & Zero-Hour Bust-Out AML Benchmark Engine (Tradeline Piggybacking & Micro-Smurfing Radar)
graph-algorithms fintech fraud-prevention aml bsa ai-agents adversary-emulation purple-team fincen credit-fraud synthetic-identity smurfing banking-security bust-out a2zsoc
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Oct 1, 2026 - Python
This project investigates the KCV-SMOTE and KFS method and its predictive performance under different proportions of unbalanced data and ratios of signal-to-noise using simulated credit transaction data.
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Apr 4, 2025 - Jupyter Notebook
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