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Which data-handling method is effective when positive examples are extremely scarce in a binary classification for detecting a rare disease?
①Evaluate with the threshold fixed at 0.5.
②Normalize all features to have zero mean and unit variance.
③Increase the minority class using synthetic oversampling methods such as SMOTE.
④Simply lower the model's learning rate.
⑤Reduce dimensionality using principal component analysis (PCA).