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Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

E. Noche

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Open access Sep 2026

Human-in-the-Loop Data Science: Enhancing Model Performance Through Interactive Learning Mechanisms

Purely automated machine learning systems often struggle to incorporate domain knowledge and contextual reasoning, resulting in reduced performance when handling ambiguous, noisy, or complex real-world data. Although existing approaches such as active learning and semi-supervised learning partially address these limita...

Isnawijayani, E. Noche, Yamini Sood et al. · 0 citations
Open access Sep 2026

Evaluating Data-Centric Optimization Strategies for Improving Machine Learning Generalization

Machine learning research has traditionally emphasized model-centric optimization, often overlooking the critical role of data quality in determining generalization performance. However, real-world datasets frequently suffer from noise, imbalance, and limited diversity, which constrain model effectiveness despite incre...

Nia Oktaviani, E. Noche, S. Patil et al. · 0 citations
Open access Sep 2026

Learning Under Extreme Class Imbalance: A Comparative Study of Algorithmic and Data-Level Solutions

A systematic comparative framework that integrates data-level resampling, cost-sensitive learning, and hybrid approaches to evaluate their performance under varying imbalance ratios and noise levels indicates that hybrid approaches consistently outperform standalone methods, achieving the most stable and balanced perfo...

Tamsir Ariyadi, E. Noche, Nisha Pandey et al. · 0 citations
Open access Sep 2026

Robust Evaluation Metrics for Assessing Machine Learning Performance Beyond Accuracy

A structured multi-metric evaluation framework that integrates classification, ranking-based, calibration, and robustness-oriented metrics for comprehensive ML performance assessment is proposed capable of supporting more reliable real-world ML deployment.

Ade Putra, E. Noche, Diksha D. Gabhane · 0 citations
Open access Sep 2026

Uncertainty-Aware Machine Learning for Reliable Decision-Making in Data-Driven Systems

An uncertainty-aware machine learning framework that integrates probabilistic modeling techniques into conventional predictive architectures to jointly estimate epistemic and aleatoric uncertainty is proposed, indicating that incorporating uncertainty estimation enhances trustworthiness and robustness without sacrifici...

Evi Yulianingsih, E. Noche, V. Yadav et al. · 0 citations

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