无监督学习：聚类分析

# -*- coding:utf-8 -*-
# /usr/bin/python
'''
@Author:  Yan Errol  @Email:2681506@gmail.com   
@Date:  2019-06-10  00:04
@Describe:
@Evn:
'''

import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from sklearn.cluster import KMeans
from scipy.spatial import Voronoi, voronoi_plot_2d

# This data set represents a toy manufacturer's product data
#
# The first value in the pair represents a toy:
#    0-2: Action Figures
#    3-5: Building Blocks
#    6-8: Cars
#
# The second value is the age group that buys the most of that toy:
#    0: 5 year-olds
#    1: 6 year-olds
#    2: 7 year-olds
#    3: 8 year-olds
#    4: 9 year-olds
#    5: 10 year-olds
x = np.array([[0,4], [1,3], [2,5], [3,2], [4,0], [5,1], [6,4], [7,5], [8,3]])

# Set up K-Means clustering with a fixed start and stop at 3 clusters
kmeans = KMeans(n_clusters=3, random_state=