Improved accuracy in predicting child health from thermal image data using logistic regression compared with J48 decision tree algorithms

Raghunath Reddy; Chinnaraj Govindasamy

doi:10.1063/5.0266037

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Improved accuracy in predicting child health from thermal image data using logistic regression compared with J48 decision tree algorithms

Raghunath Reddy Chinnaraj Govindasamy

Year: 2025 Journal: AIP conference proceedings Vol: 3267 Pages: 020128-020128 Publisher: American Institute of Physics

DOI: 10.1063/5.0266037

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Keywords:

C4.5 algorithm Decision tree Logistic regression Computer science Logistic model tree Artificial intelligence Decision tree learning Machine learning Image (mathematics) Regression Tree (set theory) Algorithm Data mining Statistics Support vector machine Mathematics Naive Bayes classifier

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Topics

Child Nutrition and Water Access

Health Sciences → Nursing → Nutrition and Dietetics

Nutritional Studies and Diet

Health Sciences → Medicine → Public Health, Environmental and Occupational Health

Energy and Environment Impacts

Physical Sciences → Environmental Science → Pollution

Improved accuracy in predicting child health from thermal image data using logistic regression compared with J48 decision tree algorithms

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