I was just wondering if there was a way to improve performance on the
one-hot encoder. Or, is there any plans to do so in the future? I am
working with a matrix that will ultimately have 20 million categorical
variables, and my bottleneck is the one-hot encoder.
Let me know if this isn't the place to inquire. My code is very simple
when using the encoder, but I cut and pasted it here for completeness.
enc = OneHotEncoder(sparse=True)
Xtrain = enc.fit_transform(tiledata)
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