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» Decision trees do not generalize to new variations
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CI
2010
93views more  CI 2010»
13 years 2 months ago
Decision trees do not generalize to new variations
Yoshua Bengio, Olivier Delalleau, Clarence Simard
FLAIRS
2006
13 years 6 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 5 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»
13 years 9 months 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 6 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