The analysis of microarray data typically involves a feature selection method in order to select the most relevant genes while at the same time maximizing the information content. This work presents a methodology that use the Welch t-test to filter the number of initial features embedded in two different frameworks to select the predictor genetic profile: genetic algorithm and stepwise forward ...

The performance of a computer-aided diagnosis system depends on the feature set used in it. This paper shows the results of image feature selection experiments. We evaluated 210 features to look for the optimum feature set. For the purpose, a forward stepwise selection approach was employed. The area under the receiver operating characteristic (ROC) curve was adopted to evaluate the performance...

Murine models with modified gene function as a result of N-ethyl-N-nitrosourea (ENU) mutagenesis have been used to study phenotypes resulting from genetic change. This study investigated genetic factors associated with red blood cell (RBC) physiology and structural integrity that may impact on blood component storage and transfusion outcome. Forward and reverse genetic approaches were employed ...

Vendor selection decisions are complicated by the fact that various conflicting multi-objective factors must be considered in the decision making process. The problem of vendor selection becomes still more compli-cated with the inclusion of incremental discount pricing schedule. Such hard combinatorial problems when solved using meta heuristics produce near optimal solutions. This paper propose...

This paper proposes two wrapper based feature selection approaches, which are single feature ranking and binary particle swarm optimisation (BPSO) based feature subset ranking. In the first approach, individual features are ranked according to the classification accuracy so that feature selection can be accomplished by using only a few top-ranked features for classification. In the second appro...

This chapter addresses strategies for selecting variables for adjustment in nonexperimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network relating treatment to outcome. While selection approaches should be based on an understanding of the causal network representing the common cause pathways between treatment and outcome, the true causal netwo...

Feature selection process is used to reduce the feature vector length and identify thediscriminative features. Many acoustic-phonetic features including Mel-Frequency CepstralCoefficient (MFCC), Energy, Pitch, Zero-crossing, spectrum were tested individually for Arabicmispronunciation detection using three classifiers; Random Forest, Bayesian classifier, BaggedSupport Vector Machine (SVM). The ...

The outage probability of dual-hop links with partial relay selection over Rayleigh fading channel in the presence of interferences is analysed. The outage expressions for amplify-and-forward (AF) and decode-and-forward (DF) relaying with relay selection, based on the instantaneous signal-to-interference ratio (SIR), are derived. Numerical results for both types of relays are presented and comp...

The goal of the WMO Expert Meeting on Agricultural Drought Indices was to move forward in the selection of a single drought index that would be used worldwide in the assessment of agricultural drought and its severity. This chapter discusses the challenges in identifying a single index to accomplish this task. Given the complexities of drought and its diverse sectoral impacts, this is a formida...