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AAAI
2006
15 years 1 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
PRICAI
2000
Springer
15 years 3 months ago
The Lumberjack Algorithm for Learning Linked Decision Forests
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...
William T. B. Uther, Manuela M. Veloso
PAMI
1998
127views more  PAMI 1998»
14 years 11 months ago
The Random Subspace Method for Constructing Decision Forests
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
Tin Kam Ho
PPSN
2004
Springer
15 years 5 months ago
Detecting and Pruning Introns for Faster Decision Tree Evolution
We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the dec...
Jeroen Eggermont, Joost N. Kok, Walter A. Kosters
AIMSA
2000
Springer
15 years 3 months ago
Classification with Belief Decision Trees
Abstract. Decision trees are considered as an efficient technique to express classification knowledge and to use it. However, their most standard algorithms do not deal with uncert...
Zied Elouedi, Khaled Mellouli, Philippe Smets