Hello All,
My dataset has 93 features and just under 62,000 observations (61,878 to be
exact). I'm running out of memory right after the mean sigma value is
computed/displayed. I've tried using dimensionality reduction via TruncatedSVD
with n_components set at different levels (78, 50 and 2 respectively) prior to
sending the data to TSNE but I still run out of memory. For TSNE,
n_components=2 and perplexity=40 (I've also tried 20). I've got 24GB of RAM on
my 64-bit windows 7 machine. Should I try a subsample of the dataset and if so,
does anyone have a recommendation on the size? Thanks!
-Jason
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