Explaining large-for-gestational-age births: a random forest classifier with a novel local interpretation method
Bioinformatics, Computational Biology and Biomedicine(2021)
摘要
ABSTRACTWe proposed a novel local interpretation method for a random forest classifier based on feature occurrence frequency in trees that give the same prediction as the random forest classifier. The method shows promising results when applied to our random forest classifier for large-for-gestational-age births. Further validation of the method is required.
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