In this paper, we present an algorithm for building ensembles of simple Bayesian classifiers in random subspaces.

As a way to try to circumvent these problems we suggest the use of an ensemble of simple Bayesian classifiers each concentrating on solving a sub-problem of the ...

In this paper, we present an algorithm for creating ensembles of simple Bayesian classifiers with feature selection using random subspaces. We consider a hill- ...

The advantages of the approach include also simplicity and speed of learning, small storage space needed during the classification, speed of classification, and ...

In this paper we present a technique for building ensembles of simple Bayesian classifiers in random subspaces. We consider also a hill-climbing-based ...

One way to gene rate an ensemble of simple Bayesian classifiers is to use different feature subsets as in the random subspace method. In this paper we present a ...

Missing: selection | Show results with:selection

In this paper we presented an algorithm for ensemble feature selection with simple. Bayesian classifiers. We considered a hill-climbing-based refinement ...

Ensembles of simple Bayesian classifiers have traditionally not been in the focus ofclassification research partly because of the stability of simple ...

Therefore, the main focus of this paper is to select useful features via proposing a wrapper feature selection approach based on a powerful genetic algorithm.