What are the potential challenges in determining the optimal values for Epsilon and MinPts in DBSCAN?
- Difficulty in selecting values that balance density and granularity of clusters
- Lack of robustness to noise
- Limited flexibility in shapes
- Risk of overfitting the data
Determining optimal values for Epsilon and MinPts in DBSCAN is challenging as it requires a careful balance between the density and granularity of clusters. Too large Epsilon can merge clusters, while too small can create many tiny clusters. Selecting MinPts affects the required density, making this tuning a complex task.
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