My understanding of boosting is just training models sequentially and learning from its previous mistakes.
Can boosting algorithms be built with bunch of logistic regression? or logistic regression + decision trees?
If yes, I would like to know some papers or books that covers this topic in-depth.
Topic boosting ensemble-modeling machine-learning
Category Data Science
Boosting is not limited to tree-based models. Find some more information here:
P. Bühlmann, T. Hothorn (2007), "Boosting Algorithms: Regularization, Prediction and Model Fitting", Statistical Science 22(4), p. 477-505.
I implemented L2 linear regression boosting from Section 3.3 (p. 483) from the paper above in this R-code. You may replace the L2 model by a logit model and see how it works.
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