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BMCBI
2008
170views more  BMCBI 2008»
15 years 2 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
Loris Nanni, Alessandra Lumini
125
Voted
ICIP
2009
IEEE
15 years 19 hour ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
112
Voted
NIPS
2004
15 years 3 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...
PRL
2002
95views more  PRL 2002»
15 years 1 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
MCS
2000
Springer
15 years 5 months ago
Combining Fisher Linear Discriminants for Dissimilarity Representations
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
Elzbieta Pekalska, Marina Skurichina, Robert P. W....