Hi Andy,
I ran it a number of times. Every once in a while, it does finish the
clustering successfully. But many times it results in the error that I have
forwarded. Anyway, for my purposes, I found that removing the init='random'
argument from the kmeans object instantiation, solves the problem. With
k-means++ it is always running successfully to completion.
Thanks,
Phani
On 24 May 2012 17:37, Andreas Mueller <[email protected]> wrote:
> Hi Phani.
> Are you sure the behavior is non-deterministic?
> I am not sure what comes out of the vectorizer,
> but my guess would be that X is a sparse matrix, which
> KMeans doesn't handle.
> Could you check that, please?
> Cheers,
> Andy
>
>
> On 05/24/2012 06:19 PM, Phani Vadrevu wrote:
>
> Hi all,
> I am trying to run some basic clustering code.
>
> vectorizer =
> CountVectorizer(preprocessor=preprocessor,token_pattern=u'/\w+/')
> # url_list is a list of strings
> X = vectorizer.fit_transform(url_list)
> print "feature extraction done in %f s"%(time() - t0)
> t0 = time()
> km = KMeans(init='random', max_iter=100,verbose=1,n_init=1)
> km.fit(X)
> print "clustering done in %f s"%(time() - t0)
>
> It runs some times, but mostly it ends in the following:
>
> feature extraction done in 0.003542 s
> Initialization complete
> Traceback (most recent call last):
> File "cluster.py", line 42, in <module>
> km.fit(X)
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/cluster/k_means_.py", line
> 735, in fit
> n_jobs=self.n_jobs)
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/cluster/k_means_.py", line
> 265, in k_means
> x_squared_norms=x_squared_norms, random_state=random_state)
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/cluster/k_means_.py", line
> 380, in _kmeans_single
> centers = _centers(X, labels, k, distances)
> File
> "/usr/local/lib/python2.7/dist-packages/sklearn/cluster/k_means_.py", line
> 507, in _centers
> centers[center_id] = X[far_from_centers[reallocated_idx]]
> ValueError: setting an array element with a sequence.
>
> What could be wrong here?
>
> Thanks,
> Phani Vadrevu
>
>
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