Training A Text Classifier Against Books

Julia Silge builds a text classifier to differentiate Pride and Prejudice from War of the Worlds:

Now it’s time to train our classification model! Let’s use the glmnet package to fit a logistic regression model with LASSO regularization. It’s a great fit for text classification because the variable selection that LASSO regularization performs can tell you which words are important for your prediction problem. The glmnet package also supports parallel processing with very little hassle, so we can train on multiple cores with cross-validation on the training set using cv.glmnet().

Hot take: Jane Austen was the best English-language novelist of the 19th century. I’d say “all-time” but the world isn’t ready for a take that hot.

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