1. DBScan

• DBScan is a density-based algorithm
• density = number of points with a specified radius (Eps)
• a point is a core point if it has more than a specified number of point (MinPts) within Eps
• There are points that are at the interior of a cluster
• A boarder point has fewer then MinPts within Eps, but is the neighborhood of a core point
• A noise point is any point that is not a core point or a boarder point.

3. Strongness v.s. Weakeness

• Strongness
• Resistant to noise
• Can handle clusters of different shapes and sizes
• Weakness
• when dataset has varying densities
• high dimensional data

4. Determine EPS and MinPts

• The idea is that for points in a cluster, their k-th nearest neighbors are at roughly the same distance
• Noise points have the kth nearest neighbor at farther distance