Computer Science · Machine Learning & Data Mining

Regarding the classification of points in DBSCAN (Density-Based Spatial Clustering of Applications with Noise), which of the following statements are CORRECT? A. Core points are defined as having at least MinPts neighbours within the specified neighbourhood radius (ε). B. Border points are instances that do not meet the core point criteria themselves but fall within the ε radius of a core point. C. Noise points are identified as outliers because they are neither core points nor located within the ε distance of any core point. D. A point is classified as a Noise point if it resides within the ε of a core point but lacks the minimum number of neighbours required to be a core point.