Hi all,
I've got a text classification problem on which LogisticRegression
consistently outperforms SGDClassifier(loss="log") by a few percentage
points on the smallish [O(10^5) points] datasets I've been using for
initial development/testing. The data set I'll ultimately be using for
training is big enough [O(10^9) to begin but incrementally increasing from
there] that I'll want to do online learning with
SGDClassifier.partial_fit()...
What I want to know is whether I can train an initial LogisticRegression
classifier, then use its coef_ to initialize a SGDClassifier(loss="log")
that would subsequently be updated via partial_fit() as new/more data come
in? Or is there stuff going on under the hood that would preclude this?
Thanks!
Fred.
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