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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