查找此K-Means模型的准确性

Question

此程序预测坐标所属的簇，它将给定点分为两个簇0和1。 如何获得该模型对变量的准确性-预测

import numpy as np  
import matplotlib.pyplot as plt  
from sklearn.cluster import KMeans  
#from sklearn.metrics import accuracy_score  
X = np.array([[1, 2],[5, 8],[1.5, 1.8],[8, 8],[6,7],[9, 11]])  
print(X)  
kmeans = KMeans(n_clusters=2)  
kmeans.fit(X)  
centroids = kmeans.cluster_centers_  
labels = kmeans.labels_  
print("Centroids :\n ",centroids)  
print("Labels    : ",labels)  
colors = ["g.","r.","c.","y."]  
for i in range(len(X)):  
print("coordinate:",X[i], "label:", labels[i])  
plt.plot(X[i][0], X[i][1], colors[labels[i]], markersize = 10)  
plt.scatter(centroids[:, 0],centroids[:, 1], marker = "x", s=150, linewidths 
= 5, zorder = 10)  
plt.show() 
prediction=kmeans.predict ( [ [ 5,6 ] ] )   
print(prediction)  

Answer 1

如果知道坐标标签的正确值，则可以使用scikit-learn's accuracy_score：

from sklearn.metrics import accuracy_score
print(accuracy_score(y_true, y_pred))

这对于群集问题确实有些棘手。考虑一下如何确定预测是否正确，并计算出准确度。