A machine learning based variable selection algorithm for binary classification of perinatal mortality

Maryam Sadiq and Ramla Shah

PLOS ONE, 2025, vol. 20, issue 1, 1-12

Abstract: The identification of significant predictors with higher model performance is the key objective in classification domain. A machine learning-based variable selection technique termed as CARS-Logistic model is proposed by coupling competitive adaptive re-weighted sampling(CARS) and logistic regression for binary classification. Based on five assessment criteria, the proposed method is found to be more efficient than Forward selection logistic regression model. The CARS-Logistic model is executed to determine the significant factors of perinatal mortality in Pakistan. The identified hazards communicated social, cultural, financial, and health-related characteristics which contain key information about perinatal mortality in Pakistan for policymakers.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0315498

DOI: 10.1371/journal.pone.0315498

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