COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Considering the K-means algorithm, after current iteration, we have 3 centroids (0, 1) (2, 1), (-1, 2). Will points (2, 3) and (2, 0.5) be assigned to the same cluster in the next iteration?
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Yes
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No
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Either A or B
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None of the above
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Explanation:
Detailed explanation-1: -In K-Means, the first centroid is selected randomly from the data points. Once the first centroid is selected, the algorithm looks for the record the furthest (in terms of Euclidean distance) in the entire data set.
Detailed explanation-2: -Initializing centroids Centroid is the center of a cluster but initially, the exact center of data points will be unknown so, we select random data points and define them as centroids for each cluster. We will initialize 3 centroids in the dataset.
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