from sklearn.cluster import KMeansimport pandas as pdf2 = list(range(0, 32)) # 32 is no of mse values below 40kmeans= KMeans(n_clusters=2).fit(X)
labels = kmeans.predict(
我有以下PCA数据,我正在对这些数据进行Kmeans聚类: PC1 PC2 PC3 PC4 PC5steelblue")pccomp.km$tot.withinss #For total within cluster sum of squares.我们还可以使用曲线图来说明数据已被排列到的组() added as a column to the original data