this paper presents a comprehensive review of the works done, during the 2000–2012, in the application of data mining techniques in credit scoring. yet there isn’t any literature in the field of data mining applications in credit scoring. using a novel research approach, this paper investigates academic and systematic literature review and includes all of the journals in the science direct onli...

This work proposes a new approach for gene expression data clustering. The technique proposed is based on a combination of two algorithms – aiNet and the minimal spanning tree (MST) – through a complementary hybrid analysis. The aiNet (Artificial Immune NETwork) [1,2] is an artificial immune system inspired by the immune network theory, originally proposed by Niels Jerne (1974) [4]. It is an it...

In this paper we present a method of hybrid predictive control (HPC) based on a fuzzy model. The identification methodology for a nonlinear system with discrete state-space variables based on combining fuzzy clustering and principal component analysis is proposed. The fuzzy model is used for HPC design, where the optimization problem is solved by the use of genetic algorithms (GAs). An illustra...

It presents some definitions of projected cluster and projected cluster group on hybrid attributes after having given some definitions on ordered attributes and sorted attributes to solve clustering analysis problem of infinite hybrid attributes data streams in finite space. In order to improve the clustering quality of hybrid attributes data streams, it presents a two-step projected clustering...

The clustering algorithm hybridization scheme has become of research interest in data partitioning applications in recent years. The present paper proposes a Hybrid Fuzzy clustering algorithm (combination of Fuzzy C-means with extension and Subtractive clustering algorithm) for data classifications applications. The fuzzy c-means (FCM) and subtractive clustering (SC) algorithm has been widely d...

Stochastic nature of earthquake has raised a challenge for engineers to choose which record for their analyses. Clustering is offered as a solution for such a data mining problem to automatically distinguish between ground motion records based on similarities in the corresponding seismic attributes. The present work formulates an optimization problem to seek for the best clustering measures. In...

Biclustering, which is simultaneous clustering of columns and rows in data matrix, became an issue when classical clustering algorithms proved not to be good enough to detect similar expressions of genes under subset of conditions. Biclustering algorithms may be also applied to different datasets, such as medical, economical, social networks etc. In this article we explain the concept beneath h...