Hello!
I am a beginner in Bayesian modelling and looking for advice on a specific implementation. I am working with small datasets and I thought that estimating priors with posteriors taken from a model trained on similar data would help (I work with languages, so training a model on a closely related model and then initiating another model with posterios).
However, my main task is to extract what factors affect the choice of answer. So, I would need some feature selection / rule extraction algorithm.
I have been looking into Bayesian Sparse Logistic Regression or adapting this tutorial. However, maybe I am missing something and there are other ways of doing that?
I would appreciate any advice!