Advances in Data Analysis and Classification

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Classification based on multivariate mixed type longitudinal data with an application to the EU-SILC database
Advances in Data Analysis and Classification - Tập 17 - Trang 369-406 - 2022
Jan Vávra, Arnošt Komárek
Although many present day studies gather data of a diverse nature (numeric quantities, binary indicators or ordered categories) on the same units repeatedly over time, there only exist limited number of approaches in the literature to analyse so-called mixed-type longitudinal data. We present a statistical model capable of joint modelling several mixed-type outcomes, which also accounts for possib...... hiện toàn bộ
Bayesian nonstationary Gaussian process models via treed process convolutions
Advances in Data Analysis and Classification - Tập 13 - Trang 797-818 - 2018
Waley W. J. Liang, Herbert K. H. Lee
The Gaussian process is a common model in a wide variety of applications, such as environmental modeling, computer experiments, and geology. Two major challenges often arise: First, assuming that the process of interest is stationary over the entire domain often proves to be untenable. Second, the traditional Gaussian process model formulation is computationally inefficient for large datasets. In ...... hiện toàn bộ
How many data clusters are in the Galaxy data set?
Advances in Data Analysis and Classification - Tập 16 - Trang 325-349 - 2021
Bettina Grün, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter
In model-based clustering, the Galaxy data set is often used as a benchmark data set to study the performance of different modeling approaches. Aitkin (Stat Model 1:287–304) compares maximum likelihood and Bayesian analyses of the Galaxy data set and expresses reservations about the Bayesian approach due to the fact that the prior assumptions imposed remain rather obscure while playing a major rol...... hiện toàn bộ
Convex clustering for binary data
Advances in Data Analysis and Classification - Tập 13 - Trang 991-1018 - 2018
Hosik Choi, Seokho Lee
We present a new clustering algorithm for multivariate binary data. The new algorithm is based on the convex relaxation of hierarchical clustering, which is achieved by considering the binomial likelihood as a natural distribution for binary data and by formulating convex clustering using a pairwise penalty on prototypes of clusters. Under convex clustering, we show that the typical $$\ell _1$$ pa...... hiện toàn bộ
Benchmarking distance-based partitioning methods for mixed-type data
Advances in Data Analysis and Classification - Tập 17 - Trang 701-724 - 2022
Efthymios Costa, Ioanna Papatsouma, Angelos Markos
Clustering mixed-type data, that is, observation by variable data that consist of both continuous and categorical variables poses novel challenges. Foremost among these challenges is the choice of the most appropriate clustering method for the data. This paper presents a benchmarking study comparing eight distance-based partitioning methods for mixed-type data in terms of cluster recovery performa...... hiện toàn bộ
Variational inference for semiparametric Bayesian novelty detection in large datasets
Advances in Data Analysis and Classification - - Trang 1-23 - 2023
Luca Benedetti, Eric Boniardi, Leonardo Chiani, Jacopo Ghirri, Marta Mastropietro, Andrea Cappozzo, Francesco Denti
After being trained on a fully-labeled training set, where the observations are grouped into a certain number of known classes, novelty detection methods aim to classify the instances of an unlabeled test set while allowing for the presence of previously unseen classes. These models are valuable in many areas, ranging from social network and food adulteration analyses to biology, where an evolving...... hiện toàn bộ
Editorial
Advances in Data Analysis and Classification - - 2011
Hans‐Hermann Bock, Wolfgang Gaul, Akinori Okada, Maurizio Vichi
Regularized logistic discrimination with basis expansions for the early detection of Alzheimer’s disease based on three-dimensional MRI data
Advances in Data Analysis and Classification - Tập 7 - Trang 109-119 - 2013
Yuko Araki, Atsushi Kawaguchi, Fumio Yamashita
In recent years, evidence has emerged indicating that magnetic resonance imaging (MRI) brain scans provide valuable diagnostic information about Alzheimer’s disease. It has been shown that MRI brain scans are capable of both diagnosing Alzheimer’s disease itself at an early stage and identifying people at risk of developing Alzheimer’s. In this article, we have investigated statistical methods for...... hiện toàn bộ
Parsimonious cluster systems
Advances in Data Analysis and Classification - Tập 3 - Trang 189-204 - 2009
François Brucker, Alain Gély
We introduce in this paper a new clustering structure, parsimonious cluster systems, which generalizes phylogenetic trees. We characterize it as the set of hypertrees stable under restriction and prove that this set is in bijection with a known dissimilarity model: chordal quasi-ultrametrics. We then present one possible way to graphically represent elements of this model.
Multiple imputation in principal component analysis
Advances in Data Analysis and Classification - Tập 5 - Trang 231-246 - 2011
Julie Josse, Jérôme Pagès, François Husson
The available methods to handle missing values in principal component analysis only provide point estimates of the parameters (axes and components) and estimates of the missing values. To take into account the variability due to missing values a multiple imputation method is proposed. First a method to generate multiple imputed data sets from a principal component analysis model is defined. Then, ...... hiện toàn bộ
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