6 Questions
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?
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?
They assume a Euclidean space.
How does the k-means algorithm handle determining the number of clusters?
It assumes the number of clusters, k, is known in advance.
What is the algorithm called that enables execution of k-means on data too large to fit in main memory?
BFR (Block-based Feature Reduction) algorithm.
How are the initial k points representing the clusters selected in a k-means algorithm?
There are several ways to select the initial k points, which will be discussed in Section 7.3.2.
Explore the concept of clustroids in cluster analysis, where a representative point is selected to define the center of a cluster. Learn about the importance of clustroids in nonEuclidean spaces and different methods for selecting them.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
