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Machine Learning Techniques for Prediction of Early Childhood Obesity
OBJECTIVES: This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. METHODS: Analyses of six different machine learning methods: RandomTree, RandomForest, J48, ID3, Naïve Bayes, and Bayes t...
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| Vydáno v: | Appl Clin Inform |
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| Hlavní autoři: | , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Schattauer
2015
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4586339/ https://ncbi.nlm.nih.gov/pubmed/26448795 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4338/ACI-2015-03-RA-0036 |
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