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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