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What does DBSCAN stand for?
How does DBSCAN group data points together?
What is one unique feature of DBSCAN in the world of machine learning?
Who were the creators of DBSCAN?
What is the main difference between DBSCAN and K-Means clustering?
What does ‘core point’ mean in DBSCAN?
What does DBSCAN do with noise or outliers in the data?
What are the two important parameters in DBSCAN?
How does DBSCAN decide if a point belongs to a group?
What is one limitation of DBSCAN?
What year was DBSCAN introduced?
Which of the following best describes the term ‘density reachability’ in DBSCAN?
In DBSCAN, if a point is not a core point or a border point, what is it classified as?
Which method can be used to determine the optimal ‘Epsilon’ value in DBSCAN?
What makes DBSCAN particularly useful for datasets with clusters of varying densities?
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