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Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, 2009
Multidimensional scaling is a technique for multidimensional data representation in a low dimensional embedding space. In this paper a multi-objective optimization approach for multidimensional scaling using evolutionary algorithms is presented. Two data sets are used for experimental investigation and results show, that this method could be useful for
Ausra Mackute-Varoneckiene +2 more
semanticscholar +5 more sources
Multidimensional scaling is a technique for multidimensional data representation in a low dimensional embedding space. In this paper a multi-objective optimization approach for multidimensional scaling using evolutionary algorithms is presented. Two data sets are used for experimental investigation and results show, that this method could be useful for
Ausra Mackute-Varoneckiene +2 more
semanticscholar +5 more sources
Nursing Research, 2008
Multidimensional scaling (MDS) is an exploratory technique used to identify unrecognized dimensions affecting behavior. Using MDS reduces large amounts of data to relatively simple, easy-to-visualize structures that reveal important relationships in an economical way and provides general solutions to many problems in perception, emotion, and cognition,
Michael A. A. Cox, Trevor F. Cox
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Multidimensional scaling (MDS) is an exploratory technique used to identify unrecognized dimensions affecting behavior. Using MDS reduces large amounts of data to relatively simple, easy-to-visualize structures that reveal important relationships in an economical way and provides general solutions to many problems in perception, emotion, and cognition,
Michael A. A. Cox, Trevor F. Cox
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Local multidimensional scaling
Neural Networks, 2006In a visualization task, every nonlinear projection method needs to make a compromise between trustworthiness and continuity. In a trustworthy projection the visualized proximities hold in the original data as well, whereas a continuous projection visualizes all proximities of the original data.
Venna, Jarkko, Kaski, Samuel
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Multigrid multidimensional scaling
Numerical Linear Algebra with Applications, 2006AbstractMultidimensional scaling (MDS) is a generic name for a family of algorithms that construct a configuration of points in a target metric space from information about inter‐point distances measured in some other metric space. Large‐scale MDS problems often occur in data analysis, representation and visualization. Solving such problems efficiently
Bronstein, M. M. +3 more
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Multidimensional Fechnerian Scaling: Basics
Journal of Mathematical Psychology, 2001Fechnerian scaling is a theory of how a certain (Fechnerian) metric can be computed in a continuous stimulus space of arbitrary dimensionality from the shapes of psychometric (discrimination probability) functions taken in small vicinities of stimuli at which these functions reach their minima. This theory is rigorously derived in this paper from three
Dzhafarov, Ehtibar N., Colonius, Hans
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A Survey on Multidimensional Scaling
ACM Computing Surveys, 2018This survey presents multidimensional scaling (MDS) methods and their applications in real world. MDS is an exploratory and multivariate data analysis technique becoming more and more popular.
Nasir Saeed +3 more
semanticscholar +1 more source
Multidimensional Scaling [PDF]
, 2004 Multidimensional scaling is a statistical technique to visualize dissimilarity data. In multidimensional scaling, objects are represented as points in a usually two dimensional space, such that the distances between the points match the observed dissimilarities as closely as possible.
Groenen, P.J.F., van de Velden, M.
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