Boosting is a class of machine learning methods based on the idea that a combination of
simple classifiers (obtained by a weak learner) can perform better than any of the simple …

With increasing number of documents in digital format, automatic text categorization has
become a crucial task in pattern recognition problems. To ease the classification task …

The curse of dimensionality is a well-known problem in pattern recognition in which the
number of patterns is smaller than the number of features in the datasets. Often, many of the …

In the framework of handwriting recognition, we present a novel GA–based feature selection
algorithm in which feature subsets are evaluated by means of a specifically devised …

World Health Organisation declared breast cancer (BC) as the most frequent suffering
among women and accounted for 15 percent of all cancer deaths. Its accurate prediction is …

Background and objective One of the most adverse conditions facing the hemodialysis
patient is repetitive hypotension during their dialysis session. Different factors can be used to …

Computer-aided drug design has become an important component of the drug discovery
process. Despite the advances in this field, there is not a unique modeling approach that can …

Feature selection for data mining optimization receives quite a high demand especially on
high-dimensional feature vectors of a data. Feature selection is a method used to select the …

Feature selection is one part of preprocessing which aims to reduce data dimensions. This
study aims to produce optimal performance of the best feature selection method …

Feature selection is one way to simplify classification process. The purpose is only the
selected features are used for classification process and without decreasing its performance …