機器學習(五) 關於散點圖生成
阿新 • • 發佈:2018-11-12
import numpy as np #隨機生成點 from sklearn.datasets import make_blobs #K-means:k均值聚類 cluster(一簇,一類) from sklearn.cluster import KMeans import matplotlib.pyplot as plt %matplotlib inline X_train,y_train = make_blobs(n_samples=150,centers=3,cluster_std=1) plt.scatter(X_train[:,0],X_train[:,1],c = y_train)#立體圖生成 plt.figure(figsize=(9,9)) axes3d = plt.subplot(projection = '3d') axes3d.scatter3D(ball['2006世界盃'],ball['2010世界盃'],ball['2007亞洲盃'],c = y_,cmap = 'rainbow') cluster_centers_ = kmeans.cluster_centers_ axes3d.scatter3D(cluster_centers_[:,0],cluster_centers_[:,1],cluster_centers_[:,2], c= [-1,3,5],cmap = plt.cm.cool,s = 300,alpha = 0.5)