In the era of healthcare, and its related research fields, the dimensionality problem of high
dimensional data is a massive challenge as it contains a huge number of variables forming …

This paper presents a comprehensive review of hybrid and ensemble-based soft computing
techniques applied to bankruptcy prediction. A variety of soft computing techniques are …

The recent developments in the modern data collection tools, techniques, and storage
capabilities are leading towards huge volume of data. The dimensions of data indicate the …

Nonlinear dimensionality reduction methods are often used to visualize high-dimensional
data, although the existing methods have been designed for other related tasks such as …

Nearest neighbor search and many other numerical data analysis tools most often rely on
the use of the euclidean distance. When data are high dimensional, however, the euclidean …

In a visualization task, every nonlinear projection method needs to make a compromise
between trustworthiness and continuity. In a trustworthy projection the visualized proximities …

Purpose: This study sought to review the characteristics, strengths, weaknesses variants,
applications areas and data types applied on the various Dimension Reduction techniques …

Human participation plays an essential role in most decisions when analyzing data. The
huge storage capacity and computational power of computers cannot replace the human …

An increasing number of the elderly population wish to live an independent lifestyle, rather
than rely on intrusive care programmes. A big data solution is presented using wearable …

The standard scientific methodology in linguistics is empirical testing of falsifiable
hypotheses. As such the process of hypothesis generation is central, and involves …