How can I implement DBSCAN clustering in Python?
You can use the DBSCAN
class from the sklearn.cluster
module. Do you have a dataset in mind?
Yes, I have a dataset with geographical coordinates. How do I start?
First, you'll need to import the necessary libraries. Here's a basic setup:
import numpy as np
import pandas as pd
from sklearn.cluster import DBSCAN
What parameters do I need to set for DBSCAN?
The main parameters are eps
(maximum distance between two samples for them to be considered in the same neighborhood) and min_samples
(the number of samples in a neighborhood for a point to be considered a core point).
Can you show me a complete example?
Sure! Here's a simple example:
from sklearn.cluster import DBSCAN
import numpy as np
# Sample data
X = np.array([[1, 2], [2, 2], [2, 3], [8, 7], [8, 8], [25, 80]])
# DBSCAN
dbscan = DBSCAN(eps=3, min_samples=2)
clusters = dbscan.fit_predict(X)
print(clusters)
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