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» Combinations of Weak Classifiers
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FLAIRS
2001
13 years 10 months ago
Time Series Analysis Using Unsupervised Construction of Hierarchical Classifiers
Recently we have proposed an algorithm of constructing hierarchical neural network classifiers (HNNC), that is based on a modification of error back-propagation. This algorithm co...
S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju...
NIPS
2004
13 years 10 months ago
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...
Vladimir Koltchinskii, Manel Martínez-Ram&o...
IJCAI
2003
13 years 10 months ago
Constructing Diverse Classifier Ensembles using Artificial Training Examples
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Prem Melville, Raymond J. Mooney
NIPS
1996
13 years 10 months ago
Effective Training of a Neural Network Character Classifier for Word Recognition
We have combined an artificial neural network (ANN) character classifier with context-driven search over character segmentation, word segmentation, and word recognition hypotheses...
Larry S. Yaeger, Richard F. Lyon, Brandyn J. Webb
PRL
2002
95views more  PRL 2002»
13 years 8 months ago
Dissimilarity representations allow for building good classifiers
In this paper, a classification task on dissimilarity representations is considered. A traditional way to discriminate between objects represented by dissimilarities is the neares...
Elzbieta Pekalska, Robert P. W. Duin