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Unsupervised Learning
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Clustering
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K-means
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411.
K-means Assignment Step
easy
How does the K-means algorithm assign samples to clusters?
A
Each sample is assigned to the cluster with the highest density of neighboring points
B
Each sample is assigned to the cluster whose centroid has the smallest angle with the sample vector
C
Each sample is assigned probabilistically based on its distance to all centroids simultaneously
D
Each sample is assigned to the cluster whose centroid is closest in Euclidean distance
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