225 search results - page 12 / 45 » On Learning Decision Trees with Large Output Domains |
120
click to vote
ML
2006
ACM
15 years 1 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 ...
190
click to vote
ICAART
2010
INSTICC
15 years 10 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...
114
click to vote
JAIR
2011
14 years 8 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...
130
click to vote
ICCV
2005
IEEE
16 years 3 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...
105
click to vote
ICML
2004
IEEE
16 years 2 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...