A comparative study demonstrates that optimized gradient boosting machine learning models reliably predict customer churn on digital health platforms by ...
A study using the Karun-I dam as a case study finds that Random Forest-based machine learning methods offer superior prediction ...
A cognitive load framework combining technical and non-technical skills ranked 190 programmers into five proficiency levels, with fine-tuned CatBoost transfer ...
A hybrid stacking ensemble of XGBoost, LightGBM and CatBoost with domain-informed features predicts concrete compressive strength with an R² of ...
Hourly smart meter readings can now reveal far more than a building's total electricity consumption. Researchers have developed COF-Tool, an ...
Machine learning can predict the dynamic alpha-zero factor governing wastewater aeration efficiency with high accuracy on random data splits, but ...
A single-center retrospective study of 702 hospitalized children with Mycoplasma pneumoniae pneumonia developed eight machine learning models that identified nine ...
A machine learning framework combining a small experimental dataset with 300 VAE-generated synthetic mixes predicts the compressive strength of recycled-concrete-powder ...
A retrospective machine learning study of 19,805 ICU patients with sepsis found that lower early serum magnesium levels were consistently ...
A study using SHAP-based explainable AI finds that US size-sorted ESG portfolios track their size benchmarks, with small-cap ESG portfolios ...
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