Journal ArticleDOI
Multidimensional scaling of interval-valued dissimilarity data
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TLDR
This method is extended to the case where dissimilarities are only known to lie within certain intervals, and shows the ability of this method to represent both the structure and the precision of dissimilarity measurements.About:
This article is published in Pattern Recognition Letters.The article was published on 2000-01-01. It has received 67 citations till now. The article focuses on the topics: Multidimensional scaling.read more
Citations
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Maximum Likelihood Estimation from Uncertain Data in the Belief Function Framework
TL;DR: This work proposes a variant of the EM algorithm that iteratively maximizes the maximization of a generalized likelihood criterion, which can be interpreted as a degree of agreement between the statistical model and the uncertain observations.
Journal ArticleDOI
Multivalued type proximity measure and concept of mutual similarity value useful for clustering symbolic patterns
TL;DR: In this paper, a novel similarity measure for estimating the degree of similarity between two patterns (described by interval type data) is proposed, which is based on a modified agglomerative method by introducing the concept of mutual similarity value.
Multivalued type proximity measure and concept of mutual ismilarity value useful for clustering symbolic patterns
TL;DR: A novel similarity measure for estimating the degree of similarity between two patterns and approximates the computed similarity value by a multivalued type data is proposed.
Journal ArticleDOI
Symbolic representation of two-dimensional shapes
TL;DR: The proposed method of shape representation and retrieval is shown to be invariant to image transformations (translation, rotation, reflection and scaling) and robust to minor deformations and occlusions.
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Principal component analysis of fuzzy data using autoassociative neural networks
TL;DR: This paper describes an extension of principal component analysis allowing the extraction of a limited number of relevant features from high-dimensional fuzzy data, and the concept of correlation coefficient is extended to fuzzy numbers, allowing the interpretation of the new features in terms of the original variables.
References
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Book
Pattern recognition and neural networks
Brian D. Ripley,N. L. Hjort +1 more
TL;DR: Professor Ripley brings together two crucial ideas in pattern recognition; statistical methods and machine learning via neural networks in this self-contained account.
Journal ArticleDOI
Nonmetric multidimensional scaling: A numerical method
TL;DR: The numerical methods required in the approach to multi-dimensional scaling are described and the rationale of this approach has appeared previously.
Pattern Recognition and Neural Networks
TL;DR: Title Type pattern recognition with neural networks in c++ PDF pattern recognition and neural networks PDF Neural networks for pattern recognition advanced texts in econometrics PDF neural networks for applied sciences and engineering from fundamentals to complex pattern recognition PDF
Book
Modern multidimensional scaling
TL;DR: Modern multidimensional scalin this paper, Modern multi-dimensional scalin, کتابخانه دیجیتال جندی شاپور اهواز