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Boosting algorithms

Expected goals in football: Improving model performance and demonstrating value

James Mead, Anthony O’Hare, Paul McMenemy

Weight Trimming and Propensity Score Weighting

Brian K. Lee, Justin Lessler, Elizabeth A. Stuart

Churn prediction of mobile and online casual games using play log data

Seungwook Kim, Daeyoung Choi, Eunjung Lee, Wonjong Rhee

Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India

Ranjit Kumar Paul, Md. Yeasin, [ ... ], Ajit Gupta

Boosting the Concordance Index for Survival Data – A Unified Framework To Derive and Evaluate Biomarker Combinations

Andreas Mayr, Matthias Schmid

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

Joanna F. Dipnall, Julie A. Pasco, [ ... ], Denny Meyer

An empirical evaluation of sampling methods for the classification of imbalanced data

Misuk Kim, Kyu-Baek Hwang

Traffic congestion prediction based on Estimated Time of Arrival

Noureen Zafar, Irfan Ul Haq

Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome

Esra Zihni, Vince Istvan Madai, [ ... ], Dietmar Frey

Stochastic gradient boosting frequency-severity model of insurance claims

Xiaoshan Su, Manying Bai

E-CatBoost: An efficient machine learning framework for predicting ICU mortality using the eICU Collaborative Research Database

Nima Safaei, Babak Safaei, [ ... ], Mahdi Moqri

Machine learning-based drought prediction using Palmer Drought Severity Index and TerraClimate data in Ethiopia

Tadele Melese, Gizachew Assefa, [ ... ], Abebe Senamew

Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting

Nathaniel MacNell, Lydia Feinstein, [ ... ], Darryl C. Zeldin

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