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» Results of the KDD'99 Classifier Learning
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FSKD
2006
Springer
124views Fuzzy Logic» more  FSKD 2006»
13 years 11 months ago
An Effective Combination of Multiple Classifiers for Toxicity Prediction
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
Gongde Guo, Daniel Neagu, Xuming Huang, Yaxin Bi
ICML
2005
IEEE
14 years 8 months ago
Ensembles of biased classifiers
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
Andreas Heß, Nicholas Kushmerick, Rinat Khou...
BMCBI
2008
114views more  BMCBI 2008»
13 years 7 months ago
Combining classifiers for improved classification of proteins from sequence or structure
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
ICML
2010
IEEE
13 years 8 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
ICML
2000
IEEE
14 years 8 months ago
Complete Cross-Validation for Nearest Neighbor Classifiers
Cross-validation is an established technique for estimating the accuracy of a classifier and is normally performed either using a number of random test/train partitions of the dat...
Matthew D. Mullin, Rahul Sukthankar