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Making Archetypal Analysis Practical
2009Archetypal analysis represents the members of a set of multivariate data as a convex combination of extremal points of the data. It allows for dimensionality reduction and clustering and is particularly useful whenever the data are superpositions of basic entities.
Christian Bauckhage, Christian Thurau
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Archetypal analysis for audio dictionary learning
2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015This paper proposes dictionary learning with archetypes for audio processing. Archetypes refer to so-called pure types, which are a combination of a few data points and which can be combined to obtain a data point. The concept has been found useful in various problems, but it has not yet been applied for audio analysis.
Aleksandr Diment, Tuomas Virtanen
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Archetypal Analysis for Population Genetics
2021Abstract The estimation of genetic clusters using genomic data has application from genome-wide association studies (GWAS) to demographic history to polygenic risk scores (PRS) and is expected to play an important role in the analyses of increasingly diverse, large-scale cohorts.
Julia Gimbernat-Mayol +3 more
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Automatic Model Selection in Archetype Analysis
2012Archetype analysis involves the identification of representative objects from amongst a set of multivariate data such that the data can be expressed as a convex combination of these representative objects. Existing methods for archetype analysis assume a fixed number of archetypes a priori.
Sandhya Prabhakaran +3 more
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A Study of Fuzzy Clustering to Archetypal Analysis
2018This paper presents a comparative study between a method for fuzzy clustering which retrieves pure individual types from data, the fuzzy clustering with proportional membership (FCPM), and an archetypal analysis algorithm based on Furthest-Sum approach (FS-AA).
Gonçalo Sousa Mendes, Susana Nascimento
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On the Use of Archetypes and Interval Coding in Sensory Analysis
2010Archetypal analysis is a statistical method aiming at synthesizing a set of multivariate observations through few points not necessarily observed. On the other hand, coding data as interval values allows to include variability and variation in the data itself.
D’Esposito M. R. +2 more
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On ill-conceived initialization in archetypal analysis
Advances in Data Analysis and Classification, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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