Computer scienceData scienceMachine learningEnsemble learning

Adaboost

Ad predictions

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Let's say we want to predict whether an online store customer will click on an ad. We have 80000 samples, with 1000 positives (the customer clicked on the ad in a session), and 79000 negatives (the customer did not click on any ads in a session).

Could AdaBoost be applied in this scenario? If so, why?

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Yes, Adaoost could be applied since the dataset seems to have enough samples

Yes, since we are working on a binary classification problem, Adaboost could be applied

No, since the dataset is highly imbalanced, the prediction accuracy for clicking on the ad will be low

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