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Fig. 4 | Malaria Journal

Fig. 4

From: Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis

Fig. 4

Prediction accuracies for different classification algorithms. Models tested include k-nearest neighbours (KNN), logistic regression (LR), support vector machines (SVM), naïve Bayes (NB), XGBoost (XGB), random forest (RF), Multilayer perceptron (MLP). Based on prediction accuracy and precision achieved, the best performing model was LR

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