How to append silhouette score to the List

Question

I want to append silhouette score to the List in the loop.

        from sklearn.cluster import KMeans
        from sklearn.metrics import silhouette_score

        ks = range(1, 11) # for 1 to 10 clusters
        #sse = []
        sil = []

        for k in ks:
             # Create a KMeans instance with k clusters: model
             kmeans = KMeans(n_clusters = k)
             # Fit model to samples
             #kmeans.fit(X)
             cluster_labels = kmeans.fit_predict(X) #X is dataset that preprocess already.
             silhouette = silhouette_score(X, cluster_labels)


             # Append the inertia to the list of inertias
             #sse.append(kmeans.inertia_)

             #Append silhouette to the list
             sil.append(silhouette)

But, I get the following error at line 21 when I set silhouette with silhouette_score

       ValueError                   Traceback (most recent call last)
       <ipython-input-12-2570ccf62502> in <module>()
       18     #kmeans.fit(X)
       19     cluster_labels = kmeans.fit_predict(X)
   --->20     silhouette = silhouette_score(X, cluster_labels)
       21 
       22

Please post the full stacktrace. But the problem here is that the silhouette score is not defined for 1 cluster. Change `ks` to be `range(2, 11)`. — Joe Halliwell, Nov 10 '19 at 09:08
@JoeHalliwell Oh, thanks i just changed range to (2,11) and it's work! — Theerapat 07, Nov 11 '19 at 10:19

score 1 · Accepted Answer · answered Nov 10 '19 at 09:47

from sklearn.datasets import make_blobs
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_samples, silhouette_score
  
X, y = make_blobs(n_samples=500,
                  n_features=2,
                  centers=4,
                  cluster_std=1,
                  center_box=(-10.0, 10.0),
                  shuffle=True,
                  random_state=1) 
sil=[]
#start the cluster range from 2
range_n_clusters = range(2,10)

for n_clusters in range_n_clusters:
    clusterer = KMeans(n_clusters=n_clusters, random_state=10)
    cluster_labels = clusterer.fit_predict(X)
    silhouette_avg = silhouette_score(X, cluster_labels)
    print("For n_clusters =", n_clusters,
          "The average silhouette_score is :", silhouette_avg)
    sil.append(silhouette_avg)

This is an example of Kmeans clustering applied to a random sample and finding the best cluster based on the silhouette score. I think this will help you or please provide much more information

I just change range to (2,11) for using silhouette, and it's work! — Theerapat 07, Nov 11 '19 at 10:21

score 0 · Answer 2 · answered Nov 10 '19 at 09:08

0

Is this the whole code or a part of it? If no code before this then it's clear that X is not defined or used before assignment.

So place the line where you assign X and things should work fine.

otherwise, please add the full trace to the error

answered Nov 10 '19 at 09:08

David Sidarous

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How to append silhouette score to the List

2 Answers2