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» Decision trees do not generalize to new variations
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CI
2010
93views more  CI 2010»
13 years 6 months ago
Decision trees do not generalize to new variations
Yoshua Bengio, Olivier Delalleau, Clarence Simard
FLAIRS
2006
13 years 10 months ago
Generalized Entropy for Splitting on Numerical Attributes in Decision Trees
Decision Trees are well known for their training efficiency and their interpretable knowledge representation. They apply a greedy search and a divide-and-conquer approach to learn...
Mingyu Zhong, Michael Georgiopoulos, Georgios C. A...
DATAMINE
1999
143views more  DATAMINE 1999»
13 years 8 months ago
Partitioning Nominal Attributes in Decision Trees
To find the optimal branching of a nominal attribute at a node in an L-ary decision tree, one is often forced to search over all possible L-ary partitions for the one that yields t...
Don Coppersmith, Se June Hong, Jonathan R. M. Hosk...
COCO
2006
Springer
118views Algorithms» more  COCO 2006»
14 years 9 days ago
Learning Monotone Decision Trees in Polynomial Time
We give an algorithm that learns any monotone Boolean function f : {-1, 1}n {-1, 1} to any constant accuracy, under the uniform distribution, in time polynomial in n and in the de...
Ryan O'Donnell, Rocco A. Servedio
ICML
1998
IEEE
14 years 9 months ago
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization
In this work, we present a new bottom-up algorithmfor decision tree pruning that is very e cient requiring only a single pass through the given tree, and prove a strong performanc...
Michael J. Kearns, Yishay Mansour