Proper selection of variables is necessary when dealing with large number of input dimensions in regression problems. In the paper, we investigate the behaviour of landscape that is formed when using Delta test as the optimization criterion. We show that simple and greedy Forward-backward selection procedure with multiple restarts gives optimal results for data sets with large number of samples...

In this paper, a global methodology for the long-term prediction of time series is proposed. This methodology combines direct prediction strategy and sophisticated input selection criteria: k-nearest neighbors approximation method (k-NN), mutual information (MI) and nonparametric noise estimation (NNE). A global input selection strategy that combines forward selection, backward elimination (or ...

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...

In this paper, we investigate the antenna and node selection issues for amplify-and-forward (AF) and decode-and-forward (DF) multi-antenna relay networks in correlated channels. Based on the channel statistics, optimal selection criteria for antenna and relay node are derived jointly, aiming to maximize the ergodic capacity. Instantaneous channel knowledge-based selection schemes, motivated by ...

Recently, considerable interest has focused on variable selection methods in regression situations where the number of predictors, p, is large relative to the number of observations, n. Two commonly applied variable selection approaches are the Lasso, which computes highly shrunk regression coefficients, and Forward Selection, which uses no shrinkage. We propose a new approach, “Forward-Lasso A...

In this paper, we adopt the relay selection (RS) protocol proposed by Bletsas, Khisti, Reed and Lippman (2006) with Enhanced Dynamic Decode-and-Forward (EDDF) and network coding (NC) system in a two-hop two-way multi-relay network. All nodes are single-input single-output (SISO) and half-duplex, i.e., they cannot transmit and receive data simultaneously. The outage probability is analyzed and w...

In contrast to feature selection and gene set analysis, bi-level selection is a process of selecting not only important gene sets but also important genes within those gene sets. Depending on the order of selections, a bi-level selection method can be classified into three categories - forward selection, which first selects relevant gene sets followed by the selection of relevant individual gen...