Maria M. Suarez-Alvarez

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Pre-processing or normalisation of data sets is widely used in a number of fields of machine intelligence. Contrary to the overwhelming majority of other normalisation procedures, when data is scaled to a unit range, it is argued in the paper that after normalisation of a data set, the average contributions of all features to the measure employed to assess(More)
BY MARIA M. SUAREZ-ALVAREZ1,*, DUC-TRUONG PHAM2,†, MIKHAIL Y. PROSTOV3 AND YURIY I. PROSTOV4 1School of Engineering, Cardiff University, Cardiff CF24 0AA, UK 2School of Mechanical Engineering, University of Birmingham, Birmingham B15 2TT, UK 3Faculty of Mechanics and Mathematics, Moscow State University, Moscow 119991, Russia 4Department of Higher(More)
BY DUC-TRUONG PHAM1,2, MARIA M. SUAREZ-ALVAREZ1,* AND YURIY I. PROSTOV3 1Manufacturing Engineering Centre, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK 2Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia 3Department of Higher Mathematics, Moscow Institute of(More)
Normalization of feature vectors is often used as a step of data preprocessing for clustering. A unified statistical approach to feature vector normalization has been proposed recently by the authors. After the proposed normalization, the contributions of both numerical and categorical attributes to a specified objective function are statistically the same.(More)
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