Titlebook: Classification and Multivariate Analysis for Complex Data Structures; Bernard Fichet,Domenico Piccolo,Maurizio Vichi Conference proceeding

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Deborah L. Mulligan,Patrick Alan Danahercuments and word counts, we employ a distribution able to model words along text considering different topics. In this regard, following Minka proposal [5], we implement a Dirichlet compound Multinomial distribution that is a mixture of random variables over words and topics. On the basis of this mo

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https://doi.org/10.1007/978-3-030-53857-6ng regions. In gray scale images this task is obtained by properly detecting, on the corresponding gray levels histogram, the valleys that space out the concentration of the pixels around the characteristic gray levels of the different image structures. In this paper, a novel procedure will be discu

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Dawne Fahey,Deborah Cunningham Breeded in conjunction with graphical tools for outlier identification. In this paper, we show that recasting FS clustering in the framework of normal mixture models can introduce some improvements: the problem of choosing a metric for clustering is avoided; membership degree is assessed by posterior prob

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A Cognitive Approach to Audio Description. (.=1,2). Comparison is based on the evaluation of the how the relational node distances evolve in the passage from the first net (..) to the second net (..). The procedure consists of two steps: (.) define an appropriate relational distance among nodes of the two networks; (.) compare the correspo

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A Cognitive Approach to Audio Descriptionportant improvement that allows a relevant saving of time or resources during computations. Histograms are a good solution, offering a good balance between computation cost and accuracy. Multidimensional data require more complicated handling in order to keep these two requirements within significan

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Ordering and Scaling Objects in Multivariate Data Under Nonlinear Transformations of Variablese transformed in the process of optimizing the objective function. Given an ordering of objects, optimal transformation of variables is guaranteed by the combined use of majorization (a particular (sub)gradient optimization method) and projection methods. The optimal sequencing is a combinatorial ta

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