问题
I have a data set with (labeled) clusters. I'm trying to find the centroids of each cluster (a vector that his distance is the smallest from all data points of the cluster).
I found many solutions to perform clustering and only then find the centroids, but I didn't find yet for existing ones.
Python schikit-learn is preferred. Thanks.
回答1:
Straight from the docs:
from sklearn.neighbors.nearest_centroid import NearestCentroid
import numpy as np
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
y = np.array([1, 1, 1, 2, 2, 2])
clf = NearestCentroid()
clf.fit(X, y)
print(clf.centroids_)
# [[-2. -1.33333333]
# [ 2. 1.33333333]]
来源：https://stackoverflow.com/questions/50332786/how-to-find-cluster-centroid-with-scikit-learn