Hi Eugene, The maxDepth parameter exists because the implementation uses Integer node IDs which correspond to positions in the binary tree. This simplified the implementation. I'd like to eventually modify it to avoid depending on tree node IDs, but that is not yet on the roadmap.
There is not an analogous limit for the GLMs you listed, but I'm not very familiar with the perceptron implementation. Joseph On Mon, Dec 14, 2015 at 10:52 AM, Eugene Morozov <evgeny.a.moro...@gmail.com > wrote: > Hello! > > I'm currently working on POC and try to use Random Forest (classification > and regression). I also have to check SVM and Multiclass perceptron (other > algos are less important at the moment). So far I've discovered that Random > Forest has a limitation of maxDepth for trees and just out of curiosity I > wonder why such a limitation has been introduced? > > An actual question is that I'm going to use Spark ML in production next > year and would like to know if there are other limitations like maxDepth in > RF for other algorithms: Logistic Regression, Perceptron, SVM, etc. > > Thanks in advance for your time. > -- > Be well! > Jean Morozov >
