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GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
15 years 10 months ago
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
Gero Szepannek, Claus Weihs
ESANN
2000
15 years 5 months ago
Influence of weight-decay training in input selection methods
We describe the results of a research on the effect of weight-decay (WD) in input selection methods based on the analysis of a trained multilayer feedforward network. It was propos...
Mercedes Fernández-Redondo, Carlos Hern&aac...
PR
2008
131views more  PR 2008»
15 years 4 months ago
A memetic algorithm for evolutionary prototype selection: A scaling up approach
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
Salvador García, José Ramón C...
ICPR
2004
IEEE
16 years 5 months ago
Selective Sampling Based on the Variation in Label Assignments
In this paper, a new selective sampling method for the active learning framework is presented. Initially, a small training set ? and a large unlabeled set ? are given. The goal is...
Piotr Juszczak, Robert P. W. Duin
WSC
1998
15 years 5 months ago
Comparison of Bayesian and Frequentist Assessments of Uncertainty for Selecting the Best System
An important problem in discrete-event stochastic simulation is the selection of the best system from a finite set of alternatives. There are many techniques for ranking and selec...
Koichiro Inoue, Stephen E. Chick