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IJPRAI
2002
93views more  IJPRAI 2002»
13 years 8 months ago
Improving Stability of Decision Trees
Decision-tree algorithms are known to be unstable: small variations in the training set can result in different trees and different predictions for the same validation examples. B...
Mark Last, Oded Maimon, Einat Minkov
GECCO
2005
Springer
195views Optimization» more  GECCO 2005»
14 years 2 months ago
Evolving fuzzy decision tree structure that adapts in real-time
A fuzzy logic algorithm has been developed that automatically allocates electronic attack (EA) resources distributed over different platforms in real-time. The controller must be ...
James F. Smith III
ISCI
2008
124views more  ISCI 2008»
13 years 8 months ago
A weighted rough set based method developed for class imbalance learning
In this paper, we introduce weights into Pawlak rough set model to balance the class distribution of a data set and develop a weighted rough set based method to deal with the clas...
Jinfu Liu, Qinghua Hu, Daren Yu
ACL
1997
13 years 10 months ago
Learning Features that Predict Cue Usage
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanatio...
Barbara Di Eugenio, Johanna D. Moore, Massimo Paol...
IJCAI
2003
13 years 10 months ago
Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction
This paper presents a novel, promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parity functions. Lookahead is the st...
David Page, Soumya Ray