DBSCAN Clustering Algorithm Solved Numerical Example in Machine Learning Data Mining by Mahesh Huddar
DBSCAN
Density-based spatial clustering of applications with noise is a data clustering algorithm
Data Points:
P1: (3, 7) P2: (4, 6)
P3: (5, 5) P4: (6, 4)
P5: (7, 3) P6: (6, 2)
P7: (7, 2) P8: (8, 4)
P9: (3, 3) P10: (2, 6)
P11: (3, 5) P12: (2, 4)
Apply the DBSCAN algorithm to the given data points and Create the clusters with minPts = 4 and epsilon (ε) = 1.9.
The following concepts are discussed:
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