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Overview of nested cross validation. We set an inner 3-Fold CV to select the best combination of hyper-parameters for training a model in the outer fold. The outer 10-Fold CV is used to evaluate the generalizability of the model. The machine learning algorithm trains the classifier using 90% of data and predicts the rest 10% data for ten times, where each data becomes the validation data once.
