1. A 2-NN (2-nearest neighbor) model is more likely to overfit than a 20-NN model. True or False? 2. Similarity measures can be incorporated into: (A) Classification trees (B) Logistic regressions (C) Hierarchical clustering (D) All of the above 3. Which of the following is NOT an issue when using k-Nearest Neighbor (k-NN)? (A) Comparing instances may not be appropriate in all contexts (B) It has trouble incorporating domain knowledge (C) Too many irrelevant attributes can influence the results (D) k-NN is difficult to compute and is not good when fast predictions are needed 4. Euclidean distance is the only feasible measure of similarity when using k-NN techniques. True or False?

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