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Uncertainty Estimation for Classification Algorithms through Confusion Matrix Analysis

Description: This technology improves upon traditional point estimates of model accuracy by implementing interval estimation techniques within Frequentist and Bayesian frameworks. Utilizing bootstrap and Monte Carlo sampling methods, it provides a robust measure of uncertainty for classification performance metrics, enhancing the reliability and interpretability...

Published: 12/16/2025 | Inventor(s): Amir Liron, Francis Méndez Mediavilla

Keywords(s): Machine Learning, Software, Statistical Analysis

Category(s): Data/AI, Software