I would like to model and predict multiple dependent variables depending on one or more independent variables. The most straightforward method appears to be multivariate regression. I was wondering though whether there are any other methods one might want to take into consideration. And does the case change if the independent variables are a mix of continuous and categorical variables?
I'm using python and mostly the sklearn package. Any advice specific to that, or other packages I might look into are also appreciated. So far I've tried using a set of linear regression models or a set of regression trees. This gives a different result from multivariate analysis (probably the depend variables are correlated), but I haven't figured out how to do that yet, I'm this functionality must've been provided somewhere.
This is the first time I'm posting a question. I didn't go into details what the data means exactly. Please let me know if there is anything I should clarify.