Advances in Data Analysis and Classification

2008 - 2026

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 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

Volume 13, issue 4, 2019

Orthogonal nonnegative matrix tri-factorization based on Tweedie distributions pp. 825-853

Hiroyasu Abe and Hiroshi Yadohisa

Discriminant analysis for discrete variables derived from a tree-structured graphical model pp. 855-876

Gonzalo Perez- de-la-Cruz and Guillermina Eslava-Gomez

Supervised learning via smoothed Polya trees pp. 877-904

William Cipolli and Timothy Hanson

Robust and sparse k-means clustering for high-dimensional data pp. 905-932

Šárka Brodinová, Peter Filzmoser, Thomas Ortner, Christian Breiteneder and Maia Rohm

Exploration of the variability of variable selection based on distances between bootstrap sample results pp. 933-963

Christian Hennig and Willi Sauerbrei

A classification tree approach for the modeling of competing risks in discrete time pp. 965-990

Moritz Berger, Thomas Welchowski, Steffen Schmitz-Valckenberg and Matthias Schmid

Convex clustering for binary data pp. 991-1018

Hosik Choi and Seokho Lee

Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership pp. 1019-1051

Gregor Zens

Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering pp. 1053-1082

Derek S. Young, Xi Chen, Dilrukshi C. Hewage and Ricardo Nilo-Poyanco

A Kendall correlation coefficient between functional data pp. 1083-1103

Dalia Valencia, Rosa E. Lillo and Juan Romo

Volume 13, issue 3, 2019

Directional co-clustering pp. 591-620

Aghiles Salah and Mohamed Nadif

Investigating consumers’ store-choice behavior via hierarchical variable selection pp. 621-639

Toshiki Sato, Yuichi Takano and Takanobu Nakahara

Subspace clustering for the finite mixture of generalized hyperbolic distributions pp. 641-661

Nam-Hwui Kim and Ryan Browne

On support vector machines under a multiple-cost scenario pp. 663-682

Sandra Benítez-Peña, Rafael Blanquero, Emilio Carrizosa and Pepa Ramírez-Cobo

Regression trees for detecting preference patterns from rank data pp. 683-702

Yu-Shan Shih and Kuang-Hsun Liu

Generalised linear model trees with global additive effects pp. 703-725

Heidi Seibold, Torsten Hothorn and Achim Zeileis

Greedy Gaussian segmentation of multivariate time series pp. 727-751

David Hallac, Peter Nystrup and Stephen Boyd

A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification pp. 753-771

Zakariya Yahya Algamal and Muhammad Hisyam Lee

Variable selection in discriminant analysis for mixed continuous-binary variables and several groups pp. 773-795

Alban Mbina Mbina, Guy Martial Nkiet and Fulgence Eyi Obiang

Bayesian nonstationary Gaussian process models via treed process convolutions pp. 797-818

Waley W. J. Liang and Herbert K. H. Lee

Volume 13, issue 2, 2019

Linear components of quadratic classifiers pp. 347-377

José R. Berrendero and Javier Cárcamo

Mixture model modal clustering pp. 379-404

José E. Chacón

A method for selecting the relevant dimensions for high-dimensional classification in singular vector spaces pp. 405-426

Dawit G. Tadesse and Mark Carpenter

Weighted distance-based trees for ranking data pp. 427-444

Antonella Plaia and Mariangela Sciandra

Mixtures of restricted skew-t factor analyzers with common factor loadings pp. 445-480

Wan-Lun Wang, Luis M. Castro, Yen-Ting Chang and Tsung-I Lin

Properties of Bangdiwala’s B pp. 481-493

Matthijs J. Warrens and Alexandra Raadt

Comparisons among several methods for handling missing data in principal component analysis (PCA) pp. 495-518

Sébastien Loisel and Yoshio Takane

A bivariate index vector for measuring departure from double symmetry in square contingency tables pp. 519-529

Shuji Ando, Kouji Tahata and Sadao Tomizawa

New distance measures for classifying X-ray astronomy data into stellar classes pp. 531-557

Amparo Baíllo, Javier Cárcamo and Konstantin Getman

Model-based approach for household clustering with mixed scale variables pp. 559-583

Christian Carmona, Luis Nieto-Barajas and Antonio Canale

Volume 13, issue 1, 2019

Special issue on “Advances on model-based clustering and classification” pp. 1-5

Sylvia Frühwirth-Schnatter, Salvatore Ingrassia and Agustín Mayo-Iscar

Unifying data units and models in (co-)clustering pp. 7-31

Christophe Biernacki and Alexandre Lourme

From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering pp. 33-64

Sylvia Frühwirth-Schnatter and Gertraud Malsiner-Walli

Clustering via finite nonparametric ICA mixture models pp. 65-87

Xiaotian Zhu and David R. Hunter

Finite mixture of regression models for censored data based on scale mixtures of normal distributions pp. 89-116

Camila Borelli Zeller, Celso Rômulo Barbosa Cabral, Víctor Hugo Lachos and Luis Benites

Finite mixture biclustering of discrete type multivariate data pp. 117-143

Daniel Fernández, Richard Arnold, Shirley Pledger, Ivy Liu and Roy Costilla

Finite mixtures, projection pursuit and tensor rank: a triangulation pp. 145-173

Nicola Loperfido

Clustering space-time series: FSTAR as a flexible STAR approach pp. 175-199

Edoardo Otranto and Massimo Mucciardi

Robust clustering for functional data based on trimming and constraints pp. 201-225

Diego Rivera-García, Luis A. García-Escudero, Agustín Mayo-Iscar and Joaquín Ortega

Assessing trimming methodologies for clustering linear regression data pp. 227-257

Francesca Torti, Domenico Perrotta, Marco Riani and Andrea Cerioli

Variable selection in model-based clustering and discriminant analysis with a regularization approach pp. 259-278

Gilles Celeux, Cathy Maugis-Rabusseau and Mohammed Sedki

Random effects clustering in multilevel modeling: choosing a proper partition pp. 279-301

Claudio Conversano, Massimo Cannas, Francesco Mola and Emiliano Sironi

sARI: a soft agreement measure for class partitions incorporating assignment probabilities pp. 303-323

Abby Flynt, Nema Dean and Rebecca Nugent

Studying crime trends in the USA over the years 2000–2012 pp. 325-341

Volodymyr Melnykov and Xuwen Zhu