Hi Phani.
It's good that you where able to work around the problem.
Could you still please open an issue on github and give a script
that reproduces the problem (non-deterministically)?
That would help us fix the problem so that other won't have the same
issue.

Thanks,
Andy


On 05/24/2012 11:53 PM, Phani Vadrevu wrote:
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] <mailto:[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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