Research for the generation of reliable recommendations has been the main goal focused
by many researchers in recent years. Though many recommendation approaches have …

Self-labeled technique, a paradigm of semisupervised classification (SSC), is highly
effective in alleviating the shortage of labeled data in classification tasks via an iterative self …

Differential evolution (DE) algorithms have demonstrated excellence performance in dealing
with global optimization problems. In DE, mutation is the sole process providing new …

Feature selection is an important task to improve prediction accuracy of classifiers and to
decrease the problem size. Several approaches have been presented to perform feature …

Differential evolution (DE) is recognized as a simple but powerful algorithm in the family of
evolutionary algorithms. Over the past two decades, many advanced DE variants with …

We here introduce a novel classification approach adopted from the nonlinear model
identification framework, which jointly addresses the feature selection (FS) and classifier …

Prototype generation deals with the problem of generating a small set of instances, from a
large data set, to be used by KNN for classification. The two key aspects to consider when …

Differential evolution (DE) is a powerful global optimization algorithm which has been
studied intensively by many researchers in recent years. A number of mutation variants have …

The main objective of this work is to develop an integrated system that is capable of
extracting precise information (knowledge) based on any stored information using the …

Evolutionary computation (EC) techniques have become popular for solving different
problems because they have powerful global search ability. Artificial bee colony (ABC) is a …