Advances in Data Analysis and Classification

2008 - 2025

Current editor(s): H.-H. Bock, W. Gaul, A. Okada, M. Vichi and C. Weihs

From:
Springer
German Classification Society - Gesellschaft für Klassifikation (GfKl)
Japanese Classification Society (JCS)
Classification and Data Analysis Group of the Italian Statistical Society (CLADAG)
International Federation of Classification Societies (IFCS)
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Volume 15, issue 4, 2021

Editorial for ADAC issue 4 of volume 15 (2021) pp. 825-828

Maurizio Vichi, Andrea Cerioli, Hans A. Kestler, Akinori Okada and Claus Weihs

PCA-KL: a parametric dimensionality reduction approach for unsupervised metric learning pp. 829-868

Alexandre L. M. Levada

Robust regression with compositional covariates including cellwise outliers pp. 869-909

Nikola Štefelová, Andreas Alfons, Javier Palarea-Albaladejo, Peter Filzmoser and Karel Hron

Learning multivariate shapelets with multi-layer neural networks for interpretable time-series classification pp. 911-936

Roberto Medico, Joeri Ruyssinck, Dirk Deschrijver and Tom Dhaene

Nonlinear dimension reduction for conditional quantiles pp. 937-956

Eliana Christou, Annabel Settle and Andreas Artemiou

Hierarchical clustering with discrete latent variable models and the integrated classification likelihood pp. 957-986

Etienne Côme, Nicolas Jouvin, Pierre Latouche and Charles Bouveyron

REMAXINT: a two-mode clustering-based method for statistical inference on two-way interaction pp. 987-1013

Zaheer Ahmed, Alberto Cassese, Gerard Breukelen and Jan Schepers

Consensus among preference rankings: a new weighted correlation coefficient for linear and weak orderings pp. 1015-1037

Antonella Plaia, Simona Buscemi and Mariangela Sciandra

Estimating the class prior for positive and unlabelled data via logistic regression pp. 1039-1068

Małgorzata Łazęcka, Jan Mielniczuk and Paweł Teisseyre

A convergent algorithm for bi-orthogonal nonnegative matrix tri-factorization pp. 1069-1102

Andri Mirzal

Volume 15, issue 3, 2021

Editorial for ADAC issue 3 of volume 15 (2021) pp. 543-546

Maurizio Vichi, Andrea Cerioli, Hans Kestler, Akinori Okada and Claus Weihs

Adaptive sparse group LASSO in quantile regression pp. 547-573

Alvaro Mendez-Civieta, M. Carmen Aguilera-Morillo and Rosa E. Lillo

A novel dictionary learning method based on total least squares approach with application in high dimensional biological data pp. 575-597

Parvaneh Parvasideh and Mansoor Rezghi

Better than the best? Answers via model ensemble in density-based clustering pp. 599-623

Alessandro Casa, Luca Scrucca and Giovanna Menardi

Sparse group fused lasso for model segmentation: a hybrid approach pp. 625-671

David Degras

A Riemannian geometric framework for manifold learning of non-Euclidean data pp. 673-699

Cheongjae Jang, Yung-Kyun Noh and Frank Chongwoo Park

Robust semiparametric inference for polytomous logistic regression with complex survey design pp. 701-734

Elena Castilla, Abhik Ghosh, Nirian Martin and Leandro Pardo

Functional data clustering by projection into latent generalized hyperbolic subspaces pp. 735-757

Alex Sharp and Ryan Browne

A bivariate finite mixture growth model with selection pp. 759-793

David Aristei, Silvia Bacci, Francesco Bartolucci and Silvia Pandolfi

Sparse principal component regression via singular value decomposition approach pp. 795-823

Shuichi Kawano

Volume 15, issue 2, 2021

Editorial for ADAC issue 2 of volume 15 (2021) pp. 261-265

Maurizio Vichi, Andrea Cerioli, Hans Kestler, Akinori Okada and Claus Weihs

M-estimators and trimmed means: from Hilbert-valued to fuzzy set-valued data pp. 267-288

Beatriz Sinova, Stefan Van Aelst and Pedro Terán

Isotonic boosting classification rules pp. 289-313

David Conde, Miguel A. Fernández, Cristina Rueda and Bonifacio Salvador

Regime dependent interconnectedness among fuzzy clusters of financial time series pp. 315-336

Giovanni De Luca and Paola Zuccolotto

Active learning of constraints for weighted feature selection pp. 337-377

Samah Hijazi, Denis Hamad, Mariam Kalakech and Ali Kalakech

A bias-variance analysis of state-of-the-art random forest text classifiers pp. 379-405

Thiago Salles, Leonardo Rocha and Marcos Gonçalves

Hierarchical conceptual clustering based on quantile method for identifying microscopic details in distributional data pp. 407-436

Kadri Umbleja, Manabu Ichino and Hiroyuki Yaguchi

Robust archetypoids for anomaly detection in big functional data pp. 437-462

Guillermo Vinue and Irene Epifanio

A perceptually optimised bivariate visualisation scheme for high-dimensional fold-change data pp. 463-480

André Müller, Ludwig Lausser, Adalbert Wilhelm, Timo Ropinski, Matthias Platzer, Heiko Neumann and Hans A. Kestler

Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions pp. 481-512

Sharon X. Lee, Tsung-I Lin and Geoffrey J. McLachlan

Clustering of modal-valued symbolic data pp. 513-541

Nataša Kejžar, Simona Korenjak-Černe and Vladimir Batagelj

Volume 15, issue 1, 2021

Editorial for ADAC issue 1 of volume 15 (2021) pp. 1-4

Maurizio Vichi, Andrea Cerioli, Hans Kestler, Akinori Okada and Claus Weihs

Interval forecasts based on regression trees for streaming data pp. 5-36

Xin Zhao, Stuart Barber, Charles C. Taylor and Zoka Milan

From-below Boolean matrix factorization algorithm based on MDL pp. 37-56

Tatiana Makhalova and Martin Trnecka

A robust spatial autoregressive scalar-on-function regression with t-distribution pp. 57-81

Tingting Huang, Gilbert Saporta, Huiwen Wang and Shanshan Wang

A combination of k-means and DBSCAN algorithm for solving the multiple generalized circle detection problem pp. 83-98

Rudolf Scitovski and Kristian Sabo

Efficient regularized spectral data embedding pp. 99-119

Lazhar Labiod and Mohamed Nadif

A cost-sensitive constrained Lasso pp. 121-158

Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez-Cobo and M. Remedios Sillero-Denamiel

A novel semi-supervised support vector machine with asymmetric squared loss pp. 159-191

Huimin Pei, Qiang Lin, Liran Yang and Ping Zhong

Kappa coefficients for dichotomous-nominal classifications pp. 193-208

Matthijs J. Warrens

Clustering discrete-valued time series pp. 209-229

Tyler Roick, Dimitris Karlis and Paul D. McNicholas

Simultaneous dimension reduction and clustering via the NMF-EM algorithm pp. 231-260

Léna Carel and Pierre Alquier

Volume 14, issue 4, 2020

Data generation for composite-based structural equation modeling methods pp. 747-757

Rainer Schlittgen, Marko Sarstedt and Christian M. Ringle

Mixtures of Dirichlet-Multinomial distributions for supervised and unsupervised classification of short text data pp. 759-770

Laura Anderlucci and Cinzia Viroli

On the use of quantile regression to deal with heterogeneity: the case of multi-block data pp. 771-784

Cristina Davino, Rosaria Romano and Domenico Vistocco

Editable machine learning models? A rule-based framework for user studies of explainability pp. 785-799

Stanislav Vojíř and Tomáš Kliegr

A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C pp. 801-819

Yanou Ramon, David Martens, Foster Provost and Theodoros Evgeniou

A process framework for inducing and explaining Datalog theories pp. 821-835

Mark Gromowski, Michael Siebers and Ute Schmid

The ultrametric correlation matrix for modelling hierarchical latent concepts pp. 837-853

Carlo Cavicchia, Maurizio Vichi and Giorgia Zaccaria

SEM-Tree hybrid models in the preferences analysis of the members of Polish households pp. 855-869

Adam Sagan and Mariusz Łapczyński

Chained correlations for feature selection pp. 871-884

Ludwig Lausser, Robin Szekely and Hans A. Kestler

Adapted single-cell consensus clustering (adaSC3) pp. 885-896

Cornelia Fuetterer, Thomas Augustin and Christiane Fuchs

Automatic gait classification patterns in spastic hemiplegia pp. 897-925

Ana Aguilera and Alberto Subero

Predicting brand confusion in imagery markets based on deep learning of visual advertisement content pp. 927-945

Atsuho Nakayama and Daniel Baier

The GNG neural network in analyzing consumer behaviour patterns: empirical research on a purchasing behaviour processes realized by the elderly consumers pp. 947-982

Kamila Migdał-Najman, Krzysztof Najman and Sylwia Badowska

Volume 14, issue 3, 2020

Editorial for ADAC issue 3 of volume 14 (2020) pp. 513-515

Maurizio Vichi, Andrea Cerioli, Hans Kestler, Akinori Okada and Claus Weihs

Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model pp. 517-542

Gerhard Tutz

Is-ClusterMPP: clustering algorithm through point processes and influence space towards high-dimensional data pp. 543-570

Khadidja Henni, Pierre-Yves Louis, Brigitte Vannier and Ahmed Moussa

Sparse classification with paired covariates pp. 571-588

Armin Rauschenberger, Iuliana Ciocănea-Teodorescu, Marianne A. Jonker, Renée X. Menezes and Mark A. Wiel

Connecting the multivariate partial least squares with canonical analysis: a path-following approach pp. 589-609

Lukáš Malec and Vladimír Janovský

A stable cardinality distance for topological classification pp. 611-628

Vasileios Maroulas, Cassie Putman Micucci and Adam Spannaus

Familywise decompositions of Pearson’s chi-square statistic in the analysis of contingency tables pp. 629-649

Rosaria Lombardo, Yoshio Takane and Eric J. Beh

Rank tests for functional data based on the epigraph, the hypograph and associated graphical representations pp. 651-676

Alba M. Franco-Pereira and Rosa E. Lillo

Enhancing techniques for learning decision trees from imbalanced data pp. 677-745

Ikram Chaabane, Radhouane Guermazi and Mohamed Hammami

Volume 14, issue 2, 2020

Special issue on “Innovations on model based clustering and classification” pp. 231-234

Christophe Biernacki, Luis Angel García-Escudero and Salvatore Ingrassia

Seemingly unrelated clusterwise linear regression pp. 235-260

Giuliano Galimberti and Gabriele Soffritti

Semiparametric mixtures of regressions with single-index for model based clustering pp. 261-292

Sijia Xiang and Weixin Yao

Gaussian parsimonious clustering models with covariates and a noise component pp. 293-325

Keefe Murphy and Thomas Brendan Murphy

A robust approach to model-based classification based on trimming and constraints pp. 327-354

Andrea Cappozzo, Francesca Greselin and Thomas Brendan Murphy

Mixture modeling of data with multiple partial right-censoring levels pp. 355-378

Semhar Michael, Tatjana Miljkovic and Volodymyr Melnykov

Gaussian mixture modeling and model-based clustering under measurement inconsistency pp. 379-413

Shuchismita Sarkar, Volodymyr Melnykov and Rong Zheng

Mixtures of skewed matrix variate bilinear factor analyzers pp. 415-434

Michael P. B. Gallaugher and Paul D. McNicholas

Data projections by skewness maximization under scale mixtures of skew-normal vectors pp. 435-461

Jorge M. Arevalillo and Hilario Navarro

ParticleMDI: particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification pp. 463-484

Nathan Cunningham, Jim E. Griffin and David L. Wild

A stochastic block model for interaction lengths pp. 485-512

Riccardo Rastelli and Michael Fop

Volume 14, issue 1, 2020

Count regression trees pp. 5-27

Nan-Ting Liu, Feng-Chang Lin and Yu-Shan Shih

Learning a metric when clustering data points in the presence of constraints pp. 29-56

Ahmad Ali Abin, Mohammad Ali Bashiri and Hamid Beigy

Clustering genomic words in human DNA using peaks and trends of distributions pp. 57-76

Ana Helena Tavares, Jakob Raymaekers, Peter Rousseeuw, Paula Brito and Vera Afreixo

Data clustering based on principal curves pp. 77-96

Elson Claudio Correa Moraes, Danton Diego Ferreira, Giovani Bernardes Vitor and Bruno Henrique Groenner Barbosa

Ensemble of optimal trees, random forest and random projection ensemble classification pp. 97-116

Zardad Khan, Asma Gul, Aris Perperoglou, Miftahuddin Miftahuddin, Osama Mahmoud, Werner Adler and Berthold Lausen

A fragmented-periodogram approach for clustering big data time series pp. 117-146

Jorge Caiado, Nuno Crato and Pilar Poncela

How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models pp. 147-173

Johannes Blömer, Sascha Brauer, Kathrin Bujna and Daniel Kuntze

Optimal arrangements of hyperplanes for SVM-based multiclass classification pp. 175-199

Víctor Blanco, Alberto Japón and Justo Puerto

Classification using sequential order statistics pp. 201-230

Alexander Katzur and Udo Kamps