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...
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...
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. ...
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...
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...