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your answer. Thanks,
Question 26 (4 points) Which of the following techniques is to guarantee that every item in the original dataset has the same chance of appearing in the training and test set. Principal component analysis (PCA) Clustering Cross-Validation Regression
Question 28 (4 points) Consider the following small set of numbers for clustering: 4; 14; 12; 6; 8. Choose 6 and 12, as initial centroids. Apply one iteration of k-means algorithm. What are the new cluster centroids after the first iteration? 6 and 12 6 and 13 8 and 13 8 and 12
Question 29 (4 points) [Multi-Select Question]: The purpose of applying Principal Component Analysis on a dataset is to help reduce the dimensions. to decorrelate the input variables. to improve the classification accuracy. to explain the variance in dependent variable.