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Fig. 1 | Parasites & Vectors

Fig. 1

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. 1

Schematic representation of the machine-learning workflow. Ten-fold cross-validation is used to assess out-of-sample performance and tune hyperparameters for each classifier. In each iteration (e.g. blue dashed box) nine folds are used for training (green) and one fold is used to assess out-of-sample performance. Next, the classifier with its optimal hyperparameters is fit on all training data before finally evaluating its performance on the validation dataset

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Parasites & Vectors

ISSN: 1756-3305

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