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From Frank Wang <>
Subject Naive Bayes vs. SGD
Date Mon, 06 Dec 2010 13:32:29 GMT

I'm working on a text classification problem. Given a piece of content, it
will be classified into 1 or more categories.
>From my understanding, Naive Bayes model is non-parametric, so every
training requires all the cumulated sample data. However, if I were to use
SGD model with n binary logistic regression, I wouldn't need to keep the
historical sample data. Which seems will lead to faster training in the long

Is this a fair logic?

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