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bro's coding
sklearn.cluster.DBSCAN 본문
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https://broscoding.tistory.com/165
머신러닝.sklearn.datasets.make_moons
from sklearn.datasets import make_moons X,y=make_moons(noise=0.1) plt.scatter(X[:,0],X[:,1],c=y)
broscoding.tistory.com
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import make_blobs,make_circles,make_moons
X,y=make_moons(noise=0.07,random_state=1)
plt.scatter(X[:,0],X[:,1],c=y,cmap='Reds')
from sklearn.cluster import DBSCAN
dbscan=DBSCAN(min_samples=3,eps=0.3)# min_samples = 3(반경안에 들어오는 셈플 수)
dbscan.fit(X)
plt.scatter(X[:,0],X[:,1],c=dbscan.labels_)
plt.colorbar()
from sklearn.cluster import DBSCAN
dbscan=DBSCAN(min_samples=9,eps=0.3) # min_samples = 9(반경안에 들어오는 셈플 수)
dbscan.fit(X)
plt.scatter(X[:,0],X[:,1],c=dbscan.labels_)
plt.colorbar()
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