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» Results of the KDD'99 Classifier Learning
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ICML
2003
IEEE
14 years 8 months ago
Tackling the Poor Assumptions of Naive Bayes Text Classifiers
Naive Bayes is often used as a baseline in text classification because it is fast and easy to implement. Its severe assumptions make such efficiency possible but also adversely af...
Jason D. Rennie, Lawrence Shih, Jaime Teevan, Davi...
IJCAI
2001
13 years 9 months ago
Using Text Classifiers for Numerical Classification
Consider a supervised learning problem in which examples contain both numerical- and text-valued features. To use traditional featurevector-based learning methods, one could treat...
Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, ...
IJON
2006
95views more  IJON 2006»
13 years 7 months ago
Ensemble classifiers based on correlation analysis for DNA microarray classification
Since accurate classification of DNA microarray is a very important issue for the treatment of cancer, it is more desirable to make a decision by combining the results of various ...
Kyung-Joong Kim, Sung-Bae Cho
INFFUS
2008
97views more  INFFUS 2008»
13 years 7 months ago
Using classifier ensembles to label spatially disjoint data
act 11 We describe an ensemble approach to learning from arbitrarily partitioned data. The partitioning comes from the distributed process12 ing requirements of a large scale simul...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
COLING
2004
13 years 7 months ago
Word Translation Disambiguation Using Bilingual Bootstrapping
This paper proposes a new method for word translation disambiguation using a machine learning technique called `Bilingual Bootstrapping'. Bilingual Bootstrapping makes use of...
Hang Li, Cong Li