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Dimensionality Reduction Hybridizations with Multi-dimensional Scaling
2016Dimensionality reduction is the task of mapping high-dimensional patterns to low-dimensional spaces while maintaining important information. In this paper, we introduce a hybrid dimensionality reduction method that is based on the weighted average of the normalized distance matrices of two or more embeddings.
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Multi-dimensional Scaling from K-Nearest Neighbourhood Distances
Journal of Scientific ComputingzbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wenjian Du, Jia Li 0008
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Internal Multi-Dimensional Scaling of Categorical Variables
1974Abstract : The purpose of the study in the dissertation is to translate raw categorized data into numerical values on which standard statistical analyses can be performed. When raw observations are recorded on a nominal scale, they are to be transformed so that the resulting numbers can be regarded as lying on an interval scale. A scalling technique is
Rolf E. Bargmann, Jeffrey Chit-Fu Chang
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The Use of Multi-Dimensional Scaling in Policy Selection
Journal of the Operational Research Society, 1982The selection of the best from a set of available policies with multi-dimensional consequences is a basic problem in decision analysis. In this paper the technique of multi-dimensional scaling is used to define a preference structure from attitude data collected from the decision maker. This data is based on a comparison of each pair of policies. Using
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E-service quality and e-retailers: Attribute-based multi-dimensional scaling
Computers in Human Behavior, 2021Prateek Kalia, Justin Paul
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Solution of multi-dimensional Fredholm equations using Legendre scaling functions
Applied Numerical Mathematics, 2020Harendra Singh +2 more
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