Classification tasks often include, among the large number of features to be processed in the
datasets, many irrelevant and redundant ones, which can even decrease the efficiency of …

Electroencephalography is a widely used clinical and research method to record and
monitor the brain's electrical activity–the electroencephalogram (EEG). Machine learning …

The nature of archaeology is complex, and is not confined to the humanistic world, but can
easily spread to scientific one. Nowadays, it is not uncommon to find archaeologists using …

Customer study is considered as an important business plan to improve the enterprise's
goal. The purpose of customer analysis is to understand the potential customer within the …

Clustering is a way of finding the structures from a collection of unlabeled gene expression
data. A number of algorithms are developed to tackle the problem of clustering the gene …

Now-a-days, data are generated massively from various sectors such as medical,
educational, commercial, etc. Processing these data is a challenging task since the massive …

This paper presents a study about the impact of evaluation criteria and similarity measures
in an unsupervisedbased feature selection (FS) method. The main aim of this paper is to …

Software fault detection is the process of analyzing the software for identifying the errors
before it is being deployed to the customer. The classifier is employed to perform the …

Abstract Jeffries-Matusita (JM) distance, a transformation of the Bhattacharyya distance, is a
widely used measure of the spectral separability distance between the two class density …

Software defect prediction (SDP) is a hot topic in the modern software engineering research
community to analyze software quality and reliability. Many data mining and machine …