Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Note: This implementation used from Iris dataset Requirements 1-Python3.6+ 2-Numpy 3-Sklearn 4-Math Run $ python3 main.py Result: In Terminal: Epsilon: 0.39 MinPoints: 4 Rate: 80.0% (Approximate) Cluster count: 3 Note: Number of all created clusters. Cluster 1th: 10 Note: Number of first cluster points. Cluster 2th: 25 Note: Number of second cluster points. Cluster 3th: 15 Note: Number of third cluster points. Noise count: 5 Note: Number of noise. Meysam Alipuor [email protected] https://github.com/ameysam/DBSCAN