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I am trying to implement a Poisson Regression in Python to predict rates. I am dealing with a ton of data (too much to store in a DataFrame), which means that using the standard statsmodels.api GLM Poisson Regression won't work. I know that sklearn has a partial_fit() method with the SGDRegressor and SGDClassifier classes for Minibatch learning, but I cannot figure out how to implement a Poisson Regression with these classes. Does anyone know how to implement a Poisson Regression with large-scale data in Python?

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