225 search results - page 23 / 45 » On Learning Decision Trees with Large Output Domains |
ICDE
2010
IEEE
13 years 12 months ago
2010
IEEE
Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key ...
JMLR
2010
13 years 2 months ago
2010
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
AIIA
2003
Springer
13 years 11 months ago
2003
Springer
The aim of this paper is to show how abduction can be used in classification tasks when we deal with incomplete data. Some classifiers, even if based on decision tree induction lik...
WWW
2011
ACM
13 years 2 months ago
2011
ACM
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
JAIR
2006
13 years 7 months ago
2006
Active learners alleviate the burden of labeling large amounts of data by detecting and asking the user to label only the most informative examples in the domain. We focus here on...