225 search results - page 12 / 45 » On Learning Decision Trees with Large Output Domains |
ML
2006
ACM
13 years 7 months ago
2006
ACM
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
ICAART
2010
INSTICC
14 years 4 months ago
2010
INSTICC
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
JAIR
2011
13 years 2 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...