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Which of the following statements about K-means clustering is true?
Which of the following statements about K-means clustering is true?
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Practice Questions
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Q1
Which of the following statements about K-means clustering is true?
It can only be applied to spherical clusters
It is guaranteed to find the global optimum
It can be sensitive to the initial placement of centroids
It does not require any distance metric
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K-means can be sensitive to the initial placement of centroids, which can lead to different clustering results on different runs.
Questions & Step-by-step Solutions
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Q
Q: Which of the following statements about K-means clustering is true?
Solution:
K-means can be sensitive to the initial placement of centroids, which can lead to different clustering results on different runs.
Steps: 5
Show Steps
Step 1: Understand what K-means clustering is. It is a method used to group data points into clusters based on their features.
Step 2: Know that K-means starts by choosing a certain number of points (called centroids) to represent the center of each cluster.
Step 3: Realize that the initial placement of these centroids can vary each time you run the K-means algorithm.
Step 4: Understand that if the centroids are placed differently at the start, the final clusters formed can also be different.
Step 5: Conclude that this sensitivity to initial placement means that K-means can produce different results on different runs.
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