Problem 3: Count Core, Border, and Noise Points

Problem Description

Write a Python program that applies DBSCAN to a dataset and counts how many points were classified as noise (label -1) versus how many belong to actual clusters.

Input

A 2D dataset with some noise expected.

Output

The count of noise points and the count of clustered points.

Constraints

• None specific.

Example Input

text
[[1,1],[1.5,1.5],[8,8],[8.5,8.5],[50,50]]

Example Output

text
Noise points: 1
Clustered points: 4

Concepts Covered

DBSCAN, counting labels, conditional filtering.