K-means是無監(jiān)督學(xué)習(xí) 聚類

#-*- coding:utf-8 -*-

import numpy as np

import matplotlib.pyplot as plt

from sklearn.cluster import KMeans

from sklearn.datasets import make_blobs

def show_kmeans():

print(__doc__)

plt.figure(figsize=(12,12))

n_samples=1500

random_state=170

x,y=make_blobs(n_samples=n_samples,random_state=random_state)

y_pred = KMeans(n_clusters=3,random_state=random_state).fit_predict(x)

plt.subplot(221)

plt.scatter(x[:,0],x[:,1],c=y_pred)

plt.title("Hello Keams")

plt.show()

if __name__ == '__main__':

show_kmeans()