如何在sklearn-python中找到K-means总迭代次数

Question

如何使用python-scikit-learn找出k-means中的迭代次数？

import pandas as pd
import csv
#from nltk.cluster import KMeansClusterer, euclidean_distance
dataset =pd.read_csv('data_akhir/sampel_akhir.csv')
X = dataset

from sklearn.cluster import KMeans
wcss = []
for i in range(1, 11):
kmeans = KMeans(n_clusters = i, init = 'k-means++', random_state=42)
kmeans.fit(X)
wcss.append(kmeans.inertia_)

kmeans = KMeans(n_clusters = 5, init = 'k-means++', random_state=42)
y_kmeans = kmeans.fit_predict(X)
file=open('data_akhir/hasil5.csv','a')
tulis=csv.writer(file,delimiter='n',lineterminator='n')
tulis.writerows([y_kmeans])
file.close()

Answer 1

使用kmeans.n_iter_获取运行的迭代次数。请参阅文档。