Can you please report this on the issue tracker? Thanks!

On 04/18/2016 09:28 AM, leg...@web.de wrote:
Thanks for your response Alexander! Here is a simplified version of my script applied to the MNIST data set. It wasn't clear from my first mail but I don't want to train it incrementally but instead apply tsne to each batch within the data set (for several epochs). This works for an unspecified number of epochs/batches until the program crashes.
for epoch in range(20)
    for batch in batch_iterator(mnist_data):
        # reshape from (500, 1, 28, 28) to (500, 784)
        data = batch.reshape(batch.shape[0], -1)
tsne = TSNE(n_components=2, random_state=0, init='pca', verbose=0).fit_transform(data)
        # continue with scatter plot visualization...
        plt.scatter(tsne[:,0], tsne[:,1], c=labels)
        plt.show()
*Gesendet:* Montag, 18. April 2016 um 14:44 Uhr
*Von:* "Alexander Fabisch" <afabi...@informatik.uni-bremen.de>
*An:* scikit-learn-general@lists.sourceforge.net
*Betreff:* Re: [Scikit-learn-general] tSNE assertion errors
Hi Sarah,

t-SNE does not support incremental training. Your model will be retrained every time you fit a new batch of data (see https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/manifold/t_sne.py#L664). That means you might have found a dataset that reveals an error in implementation. Could you provide a small script that reproduces the error?

Best regards,

Alexander
Am 18.04.2016 um 14:28 schrieb leg...@web.de:

    Hey everyone!
    I am new to Python and the scikit learn package so I hope someone
    can help me with the two issues I encountered during use of the
    sklearn.manifold implementation of the t-SNE algorithm. First a
    little bit of context: I am repeatedly feeding batches of
    dimensionality 500x784 to the algorithm for visualization.
    However, before my script finishes, one of the two following error
    messages occurs:
    AssertionError:[t-SNE]Insertionfailed
    or
    AssertionError:Treeconsistency failed:unexpected number of
    points=499at root node=500
    Furthermore, these messages do not occur at a fixed time but their
    behaviour seems rather non-deterministic. Hopefully someone came
    across this problem before and can help me to fix it.
    Best,
    Sarah

    
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