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Because we selected machine learning models with different inductive biases, we explored an ensemble method voting classifier. The estimators for the voting classifier include all of the ML models described previously: logistic regression, random forests, SVM, and k-NN. In addition, soft voting was performed using average predicted probabilities to predict class labels.
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