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IJAR
2010
189views more  IJAR 2010»
13 years 6 months ago
A fuzzy random forest
Following Breiman’s methodology, we propose a multi-classifier based on a “forest” of randomly generated fuzzy decision trees, i.e., a Fuzzy Random Forest. This approach co...
Piero P. Bonissone, José Manuel Cadenas, M....
DIS
2001
Springer
14 years 3 days ago
Functional Trees
In the context of classification problems, algorithms that generate multivariate trees are able to explore multiple representation languages by using decision tests based on a com...
Joao Gama
NLP
2000
13 years 11 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
IJCAI
2003
13 years 9 months ago
Inductive Learning in Less Than One Sequential Data Scan
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo
CORR
2010
Springer
74views Education» more  CORR 2010»
13 years 7 months ago
Significance of Classification Techniques in Prediction of Learning Disabilities
The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age chil...
Julie M. David, Kannan Balakrishnan