kkirchheim/mchad
🔎 Multi-Class Hypersphere Anomaly Detection (ICPR)
This project helps machine learning practitioners identify unusual or anomalous data points within multi-class datasets. It takes labeled images and their corresponding categories as input and outputs predictions that distinguish between typical data and outliers. Data scientists and machine learning engineers working on classification problems will find this useful for improving model robustness.
No commits in the last 6 months.
Use this if you need to reliably detect data points that don't fit into any of your predefined categories in a classification task.
Not ideal if your primary goal is standard multi-class classification without a specific need for anomaly detection.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Jun 04, 2024
Commits (30d)
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