Currently, we are working on a school project which is trying to predict the number of crimes in some area/neighbourhood.
There are 8 different categories for crimes and we've tried to find the correlation among those categories and now we only have 4 left. Instead of building a model for each category, we want to predict these 4 categories simultaneously by some multi-output algorithm.
Our sample size is around 27,000 for 6 years (from 2011 to 2016, 4000+ for each year). We are going to use (maybe) cross-validation to build/test our model.
Would you please list 2-3 algorithms which already have fully or partially implemented library in Python (preferred) or R you would recommend to use with our dataset scale? I only found scikit-learn with this algorithm. But it's for classification rather then prediction numbers.
This is a intro-level ML course project, the group is not very experienced in the field and the time is limited so we don't want to implement an algorithm from scratch.