CO2 Forest: Improved Random Forest by Continuous Optimization of Oblique Splits

19 Jun 2015Mohammad NorouziMaxwell D. CollinsDavid J. FleetPushmeet Kohli

We propose a novel algorithm for optimizing multivariate linear threshold functions as split functions of decision trees to create improved Random Forest classifiers. Standard tree induction methods resort to sampling and exhaustive search to find good univariate split functions... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.