Leveraging Persistent Homology for Topological Feature Extraction in Machine Learning: The PH-AML Pipeline
PHAML enhances machine learning by integrating topological features from persistent homology with traditional data inputs, capturing global structure through Vietoris–Rips filtrations. This approach improves classification accuracy and robustness compared to baseline models using only conventional features.
Apr 1, 2025
