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in the README.md,I see I found I get many cluster(>300) with you code. How to adjust the result? my test code is below
import matplotlib.pyplot as plt import numpy as np from sklearn.datasets import make_circles from sklearn.preprocessing import StandardScaler import pyrcc from sklearn.metrics import adjusted_mutual_info_score n_samples = 1500 noisy_circles =make_circles(n_samples=n_samples, factor=.5,noise=.05) X = noisy_circles[0] #X = StandardScaler().fit_transform(X) Y = noisy_circles[1] clusterer = pyrcc.RccCluster(measure='cosine') P = clusterer.fit(X) print('AMI: {}'.format(adjusted_mutual_info_score(Y, P))) print(np.unique(P))
the result is below
The text was updated successfully, but these errors were encountered:
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in the README.md,I see
I found I get many cluster(>300) with you code. How to adjust the result?
my test code is below
the result is below
The text was updated successfully, but these errors were encountered: