Random Forest machine learning method
We used Random Forest (RF) for data integration and individual data set
analysis. RF is a machine learning ensemble method in conjunction with
multiple learning algorithms to obtain better predictive
performance18. RF can be used for both classification
and regression. In our analysis we used RF for classification using the
feeding method (exclusively breastfed vs exclusively formula-fed) as
outcome variable and treating each of the data sets separately. We used
ntree = 500 and mtry = square root of variables in our models. We used
two packages for RF analysis (randomForest and varSelRF) in R (v3.6.1).