Python K-medoids可視化

Question

我從互聯網上得到的這段代碼。我適用於我的數據和工作。所以我試圖展示這種方法的可視化，但我無法找到k-medoids的相關可視化代碼。

from nltk.metrics import distance as distance 
import Pycluster as PC 
words = ['apple', 'Doppler', 'applaud', 'append', 'barker', 
    'baker', 'bismark', 'park', 'stake', 'steak', 'teak', 'sleek'] 
dist = [distance.edit_distance(words[i], words[j]) 
    for i in range(1, len(words)) 
    for j in range(0, i)] 

clusterid, error, nfound = PC.kmedoids(dist, nclusters=3) 
cluster = dict() 

uniqid=list(set(clusterid)) 
new_ids = [ uniqid.index(val) for val in clusterid] 
for word, label in zip(words, clusterid): 
    cluster.setdefault(label, []).append(word) 
for label, grp in cluster.items(): 
    print(grp) 

Answer 1

你輸入數據字。

你會如何想象它們？它們不是座標向量。