重复步骤2和3,直到聚类中心的变化小于设定的阈值,或达到最大迭代次数。 三、Python实现示例 接下来,我们将使用Python实现FCM算法,并且使用numpy和matplotlib库进行数据处理和可视化。 代码示例 AI检测代码解析 importnumpyasnpimportmatplotlib.pyplotaspltclassFuzzyCMeans:def__init__(self,n_clusters=3,m=2,max_iter...
train_error =1- np.sum(np.abs(trainLabels_prediction - trainLabels)) / trainLength test_error =1- np.sum(np.abs(testLabels_prediction - testLabels)) / (dataX.shape[0] - trainLength)print("Clustering on traintset is %.2f%%"% (train_error*100))print("Clustering on testset is %....
下面是使用Python实现模糊C均值聚类算法的示例代码: importnumpyasnp deffuzzy_cmeans_clustering(X, n_clusters, m=2, max_iter=100, tol=1e-4): # 初始化聚类中心 centroids=X[np.random.choice(range(len(X)), size=n_clusters)] # 迭代更新 for_inrange(max_iter): # 计算隶属度 distances=np.li...
(python) bias variance tradeoff – clearly explained complete introduction to linear regression in r caret package – a practical guide to machine learning in r logistic regression – a complete tutorial with examples in r principal component analysis (pca) – better explained k-means clustering ...
K-均值聚类(K-means clustering)何时使用?...工作方式该算法可以随机将每个观测值(observation)分配到 k 类中的一类,然后计算每个类的平均。接下来,它重新将每个观测值分配到与其最接近的均值的类别,然后再重新计算其均值。...更加细微的细节:上面所描述的算法还有一些变体。最初的「种子」聚类可以通过多种方式...
ax0.set_title('Test data: 200 points x3 clusters.')#plt.show()#Set up the loop and plotalldata =np.vstack((xpts, ypts))#print alldata#Regenerate fuzzy model with 3 cluster centers - note that center ordering#is random in this clustering algorithm, so the centers may change places#使...
(u,axis=0)# 绘制结果foriinrange(n_clusters):plt.scatter(data[cluster_labels==i,0],data[cluster_labels==i,1],label=f'Cluster{i}')# 绘制簇心plt.scatter(cntr[:,0],cntr[:,1],s=300,c='red',label='Centroids',marker='X')plt.title('Fuzzy C-Means Clustering')plt.legend()plt....
cluster_labels.append(idx)returncluster_labelsdeffuzzyCMeansClustering():# 主程序membership_mat = initializeMembershipMatrix() curr =0start = time.time()# 开始时间,计时whilecurr <= MAX_ITER:# 最大迭代次数cluster_centers = calculateClusterCenter(membership_mat) ...
模糊C均值聚类(Fuzzy C-Means,FCM)是一种广泛应用的聚类算法,允许数据点以不同的隶属度属于多个簇。以下是对模糊C均值聚类的详细解答,包括其基本原理、Python实现以及测试和优化建议。 1. 模糊C均值聚类的基本原理 模糊C均值聚类旨在通过最小化目标函数来发现数据集中的潜在聚类结构。目标函数通常定义为: markdown ...
Possiblistic Fuzzy C-Means Algorithm in Python Algorithm explanation :https://www.researchgate.net/publication/3336300_A_Possibilistic_Fuzzy_C-Means_Clustering_Algorithm Implementation of the algorithm MATLAB :https://www.ijser.org/researchpaper/implementation-of-possibilistic-fuzzy-cmeans-clustering-algorit...