This program was made to visualize MLLib Random Forests. Running this program with a supplied trees file generates
visual version of the trees. You can get this from printing out the debug string of the generated model. In python that is:
model.toDebugString()
Run:
python eurekatrees.py --trees ./sample_files/trees.txt
If you have a csv with the names of your features you can run that command with the columns switch.
python eurekatrees.py --trees ./sample_files/trees.txt --columns ./sample_files/columns.csv
The output are a bunch of HTML files. If you open up the file home.html it should allow you to easily navigate to each of your trees.
Important Note:
The last change that was made splays out branches further which means more scrolling for right now, but I am looking into d3 canvas zooming to fit it to the page then allow the user to move around inside of the canvas. If anybody have any experience with doing this feel free to contribute or pass along any tips. Thanks!
Example Tree:
Credit D3.js tree example from http://bl.ocks.org/d3noob/8326869 was a great help.