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What is DBSCAN primarily used for in clustering?
Practice Questions
Q1
What is DBSCAN primarily used for in clustering?
To find spherical clusters
To identify noise and outliers
To classify data points
To reduce dimensionality
Questions & Step-by-Step Solutions
What is DBSCAN primarily used for in clustering?
Steps
Concepts
Step 1: Understand that DBSCAN is a clustering algorithm used in data analysis.
Step 2: Know that it groups data points into clusters based on their density.
Step 3: Recognize that DBSCAN can find clusters of different shapes, not just round ones.
Step 4: Learn that it can also identify noise, which are points that do not belong to any cluster.
Step 5: Conclude that DBSCAN is useful for discovering patterns in data while ignoring irrelevant points.
No concepts available.
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