Usage example

import warnings
warnings.simplefilter("ignore")
from shared_nearest_neighbors import SNN
import matplotlib.pyplot as plt
from sklearn.datasets import make_classification
import numpy as np

X, y = make_classification(n_samples=2500, n_features=2, n_classes=4, n_informative=2, n_redundant=0, n_repeated=0, n_clusters_per_class=1,
class_sep=3)

keep = 200
X, y = X[:keep], y[:keep]

plt.scatter(X[:, 0], X[:, 1])

<matplotlib.collections.PathCollection at 0x7ff52fb92430>

snn = SNN(n_neighbors=30, eps=15, min_samples=25)
snn.fit(X)
plt.scatter(X[:, 0], X[:, 1], c=snn.labels_)
plt.plot()

[]