Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package
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Updated
Aug 16, 2024 - C
Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package
UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.
This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets
In this repo, different techniques will be done to analyze Anomaly detection
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.
Deriving the Local Outlier Factor Score
Laws of Form - Complete Corpus of Definitions - To use in LLMs - ChatGPT 4o - Claude
To detect Credit Card Fraud by using SVR, Isolation Forest and Local Outlier Factor.
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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