Is anyone aware whether someone has produced a cheatsheet--preferably like a summary table--of various machine learning techniques (e.g. kNN, regression tree, Naive Bayes, linear regression, neural nets, etc.) along with the type of dependent and independent variables they accept (continuous, categorical, binary, etc.)?
I realize there can be a lot of shifty grey area here, but a general guide of some sort could be helpful for becoming familiar with these tools. I've done a lot googling not turned up anything like this yet.
Cheers
