What role does 'MinPts' play in the DBSCAN algorithm?
- Minimum Distance Between Points
- Minimum Percentage of Cluster Separation
- Minimum Points to Form a Cluster
- Minimum Potential for a Cluster
'MinPts' in DBSCAN refers to the minimum number of points required to form a dense region. It's used in conjunction with the Epsilon parameter to decide whether a particular region can be considered a cluster. It controls the density requirement for clustering, determining how many points must be within the Epsilon radius for a region to be considered dense.
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