Feature selection is an importance step in classification phase and directly affects the classification performance. Feature selection algorithm explores the data to eliminate noisy, redundant, irrelevant data, and optimize the classification performance. This paper addresses a new subset feature selection performed by a new Social Spider Optimizer algorithm (SSOA) to find optimal regions of th...

We propose a fully automated algorithm that is able to select a discriminative feature set from a training database via sequential forward selection (SFS), sequential backward selection (SBS), and F-score methods. We applied this scheme to microcalcifications cluster (MCC) detection in digital mammograms for early breast cancer detection. The system was able to select features fully automatical...

A diagnostic method along the lines of forward search is proposed to simultaneously study the effect of individual observations and features on the inferences made in linear regression. The method operates by appending dummy variables to the data matrix and performing backward selection on the augmented matrix. It outputs sequences of feature–outlier combinations which can be evaluated by plots...

BACKGROUND In body surface potential mapping, increased spatial sampling is used to allow more accurate detection of a cardiac abnormality. Although diagnostically superior to more conventional electrocardiographic techniques, the perceived complexity of the Body Surface Potential Map (BSPM) acquisition process has prohibited its acceptance in clinical practice. For this reason there is an inte...

Quality and safety of foods is one of the world’s top topics. Using high-precision spectral devices is a main technology trends by its high accuracy and nondestructive of food inspection, but the common obstacle is how to extract informative variables from raw data without losing significant information. This article proposes a novel feature selection algorithm named Support Vector Machine-Mult...

Wind power prediction (WPP) of wind farm clusters is important to the safe operation and economic dispatch system, but it faces two challenges: (1) The dimensions input parameters for WPP are very high so that contain irrelevant or redundant features; (2) difficult build a holistic model with high-dimensional clusters. To overcome these challenges, novel short-term clusters, based on sequential...