题目
BU.330.775.T2.FA25 Final- Requires Respondus LockDown Browser
单项选择题
Which of the following statements about the K-means clustering algorithm is true?
选项
A.K-means clustering assigns each data point to the cluster with the farthest centroid.
B.K-means randomly places data points into groups and never updates them.
C.Inertia in K-means always increases as the number of clusters (K) increases.
D.The elbow method helps decide how many groups (K) to use by looking for a point where adding more groups doesn’t improve the fit significantly.
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标准答案
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思路分析
Question: Which of the following statements about the K-means clustering algorithm is true?
Option 1: 'K-means clustering assigns each data point to the cluster with the farthest centroid.' This is incorrect. K-means assigns each data point to the nearest centroid (i.e., the closest cluster center) to minimize within-cluster variance, not the farthest one.
Option 2: 'K-means rand......Login to view full explanation登录即可查看完整答案
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类似问题
K-Means involves computing distances in input space and assigning data points to the nearest prototype points. What can one say about these prototype points? I Every cluster has its data assigned to the nearest prototype point. II They are not restricted to being data points in the training set. III They are necessarily included in the training set. IV They are usually referred to as centroids.
A retail chain wants to group its 2 million customers based on purchase behavior. Analysts consider using K-Means because they need fast runtime and easy interpretability, but the leadership team worries whether the method assumes overly simple cluster shapes. What limitation of K-Means should the team be most concerned about?
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Question14 Which of the following aspects do not affect the performance of the standard k-means clustering? (you can choose more than one) Choice of initial cluster centres Probability of data samples belonging to each cluster Distribution of data samples Number of clusters ResetMaximum marks: 1.5 Flag question undefined
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