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» Improving Stability of Decision Trees
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FLAIRS
2004
13 years 11 months ago
Inducing Fuzzy Decision Trees in Non-Deterministic Domains using CHAID
Most decision tree induction methods used for extracting knowledge in classification problems are unable to deal with uncertainties embedded within the data, associated with human...
Jay Fowdar, Zuhair Bandar, Keeley A. Crockett
IJAR
2007
87views more  IJAR 2007»
13 years 9 months ago
Pruning belief decision tree methods in averaging and conjunctive approaches
The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interp...
Salsabil Trabelsi, Zied Elouedi, Khaled Mellouli
ICML
1996
IEEE
14 years 1 months ago
Second Tier for Decision Trees
A learner's performance does not rely only on the representation language and on the algorithm inducing a hypothesis in this language. Also the way the induced hypothesis is ...
Miroslav Kubat
COMSIS
2006
156views more  COMSIS 2006»
13 years 9 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
ICML
2004
IEEE
14 years 10 months ago
Sequential skewing: an improved skewing algorithm
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
Soumya Ray, David Page