16 lines
464 B
Python
16 lines
464 B
Python
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
from sklearn.cluster import DBSCAN
|
|
from sklearn.datasets import make_moons
|
|
|
|
# Erzeuge einen Beispieldatensatz
|
|
data, _ = make_moons(n_samples=300, noise=0.05, random_state=0)
|
|
|
|
# Anwendung von DBSCAN
|
|
dbscan = DBSCAN(eps=0.3, min_samples=5)
|
|
predicted_labels = dbscan.fit_predict(data)
|
|
|
|
# Visualisierung
|
|
plt.scatter(data[:, 0], data[:, 1], c=predicted_labels, cmap='viridis')
|
|
plt.title('DBSCAN-Clustering')
|
|
plt.show() |