225 search results - page 2 / 45 » On Learning Decision Trees with Large Output Domains |
IJCAI
1989
13 years 7 months ago
1989
A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the arti...
SSPR
1998
Springer
13 years 10 months ago
1998
Springer
Properly addressing the discretization process of continuos valued features is an important problem during decision tree learning. This paper describes four multi-interval discreti...
NLP
2000
13 years 9 months ago
2000
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
ECML
2007
Springer
13 years 10 months ago
2007
Springer
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
PRICAI
2000
Springer
13 years 9 months ago
2000
Springer
While the decision tree is an effective representation that has been used in many domains, a tree can often encode a concept inefficiently. This happens when the tree has to repres...