Built a model to detect fraudulent credit card transactions so that the customers of credit card companies are not charged for items that they did not purchase.
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Updated
Dec 23, 2021 - Jupyter Notebook
Built a model to detect fraudulent credit card transactions so that the customers of credit card companies are not charged for items that they did not purchase.
To detect Credit Card Fraud by using SVR, Isolation Forest and Local Outlier Factor.
Deriving the Local Outlier Factor Score
Complete Corpus of Definitions to play with George Spencer Brown's Laws of Form in ChatGPT
Recognition of anomalies in the data stream in real time. Identify peaks. Fraud detection.
Local Outlier Factor (LOF), a density-based outlier detection technique to find frauds in credit card transactions.
In this repo, different techniques will be done to analyze Anomaly detection
This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets
UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.
Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package
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