Feature selection plays a central role in data analysis and is also a crucial step in machine learning, data mining and pattern recognition. Feature selection algorithm focuses mainly on the design of a criterion function and the selection of a search strategy. In this paper, a novel feature selection approach (NFSA) based on quantum genetic algorithm (QGA) and a good evaluation criterion is pr...

In this paper, we investigate an opportunistic relay and jammer scheme along with relay selection algorithms based on the secrecy rate criterion in multiple-input multiple-output buffer-aided down link relay networks, which consist of one source, a number of relay nodes, legitimate users and eavesdroppers, with the constraints of physical layer security. The opportunistic relay and jammer schem...

In this paper we propose a simple non-parametric model for multiple crite-ria supplier selection problem. The proposed model does not generate a zeroweight for a certain criterion and ranks the suppliers without solving the modeln times (one linear programming (LP) for each supplier) and therefore allowsthe manager to get faster results. The methodology is illustrated using anexample.

The ordinary Bayes information criterion is too liberal for model selection when the model space is large. In this article, we re-examine the Bayesian paradigm for model selection and propose an extended family of Bayes information criteria. The new criteria take into account both the number of unknown parameters and the complexity of the model space. Their consistency is established, in partic...

State filters can be used to produce online estimates of the state of a process. If an exact model for the true process is not known, but multiple candidate models are available to describe the current behavior of the true system, it is necessary to select that model that leads to the optimal state estimates. This paper describes a novel approach for model selection for state estimation by comp...

Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of generalisation performance, such as k-fold cross-validation. The error of such an estimator can be broken down into bias and variance components. While unbiasedness is often cited as a beneficial quality of a model se...

This paper proposes a model selection criterion for classification problems. The criterion focuses on selecting models that are discriminant instead of models based on the Occam’s razor principle of parsimony between accurate modeling and complexity. The criterion, dubbed Discriminative Information Criterion (DIC), is applied to the optimization of Hidden Markov Model topology aimed at the reco...

Template selection is an important step in a feature based electronic digital image stabilizer (EDIS). In this paper, we present a wavelet-based criterion for template locating that can be used in block-based electronic digital image stabilizers. Tlus criterion computes the vertical and horizontal details of an image and employs them for template selection. The performance of this criterion is ...