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. 2020 Feb 4;10:1776. doi: 10.1038/s41598-020-58601-7

Figure 5.

Figure 5

Top 50 most predictive register feature vector features from the best gradient boosting model ranked by their importance and colour-coded according to type (x-axis). Feature importance is a normalized estimate of a relative contribution of the feature to the model prediction (y-axis). Drug prescription features had the highest overall cumulative importance followed by the canonical features and hospital diagnoses. Age, interaction between age and sex, and date of first T2D diagnoses were the three most important features for all comorbidities.