K-means clustering
12 important questions on K-means clustering
What is the semantical value of a distance in the context of clustering?
And it is the leading metric on deciding items to belong together
What is a feature vector?
What is a similarity function?
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What is the target/goal a K-means clustering algorithm aims to achieve?
Why use heuristic functions when computing a K-Means clustering?
What is the trade-off for applying a heuristic function when computing a clustering with a K-Means algorithm?
What are the three steps in the K-Means clustering algorithm?
Assignment
Update
What happens in the assignment-step in the K-Mean algorithm?
What happens in the update-step in the K-Means algorithm?
When do we achieve convergence in the iterative process of the K-Means algorithm?
And the cluster centers did not move either
Name three approaches of initiating K-Means cluster centers.
Random data points
Randomly label points and derive initial cluster centers from that
Neglecting the possibility of local minima, what are two guaranteed shortcomings of a clustering result with the K-Means algorithm?
Data points are strictly categorized with a single label, even though
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