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What is the criterion for selecting the clustroid in a cluster?
What is the criterion for selecting the clustroid in a cluster?
The point with the minimum sum of distances to the other points in the cluster.
In the context of clustering with edit distance, how does choosing the clustroid by minimizing the sum of distances differ from minimizing the maximum distance?
In the context of clustering with edit distance, how does choosing the clustroid by minimizing the sum of distances differ from minimizing the maximum distance?
Choosing by minimizing the sum of distances may result in one point as the clustroid, while minimizing the maximum distance may lead to another point becoming the clustroid.
What is the main assumption made by k-means algorithms regarding the space?
What is the main assumption made by k-means algorithms regarding the space?
They assume a Euclidean space.
How does the k-means algorithm handle determining the number of clusters?
How does the k-means algorithm handle determining the number of clusters?
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What is the algorithm called that enables execution of k-means on data too large to fit in main memory?
What is the algorithm called that enables execution of k-means on data too large to fit in main memory?
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How are the initial k points representing the clusters selected in a k-means algorithm?
How are the initial k points representing the clusters selected in a k-means algorithm?
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