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Module 4: Hypothesis Testing and Ensemble Methods

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AdaBoost primarily focuses subsequent learners on (i) Randomly selected features only (ii) Previously misclassified or difficult observations (iii) Only correctly classified observations (iv) Unlabelled observations

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Answer: (ii) Previously misclassified or difficult observations

AdaBoost increases the weights of incorrectly classified training examples so subsequent weak learners pay more attention to them. Learners are combined using weights based on their performance.

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