I’m working with online stats to learn a classification model. I have a sparse array of tfidf features and binary target variables and have figured out how to train my model. The API documentation is lacking and needs to include how to use the regularization functions.
Specifically, I need to know how to adjust the parameter lambda.
I also need to know if a bias term is added automatically or if I need to do this. So far I have the following:
using OnlineStats o = fit!(StatLearn(length(feature_array), SGD(), L1Penalty()), (train_tfidf, train_y))
StatLearn: SGD | mean(λ)=0.0 | 0.5 * (L2DistLoss) | L1Penalty | nobs=7782 | nvars=2446
I can gather predictions using:
test_y_pred = predict(o, test_tfidf)
I can classify them using:
test_y_pred = classify(o, test_tfidf)