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Fig. 3 | Parasites & Vectors

Fig. 3

From: Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data

Fig. 3

Decision tree classifier. The top line shows the condition for descending the tree. Blue leaves imply the model predicts a positive B. canis infection, whereas orange leaves predict no infection. Samples refers to the total number of samples from the training set that end up in a particular leaf. Values are the weighted samples in a leaf, where the first entry corresponds to the negative samples (which have a weight of ~ 0.54) and the second entry to the positive samples (with a weight of ~ 7.07). Whichever value is largest determines the leaf label. Note that the complete right branch only contains one positive sample in the train set. As such, the parameter abs_lymphs(× 10E9 cells/l) is plausibly of lesser importance, despite it being high up in the tree

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Parasites & Vectors

ISSN: 1756-3305

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