| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A between-cluster approach for clustering skew-symmetric data
|
Vicari, Donatella
|
|
|
|
1 |
p. 163-192
|
artikel
|
| 2 |
A combination of k-means and DBSCAN algorithm for solving the multiple generalized circle detection problem
|
Scitovski, Rudolf
|
|
|
|
1 |
p. 83-98
|
artikel
|
| 3 |
A comparison of reliability coefficients for psychometric tests that consist of two parts
|
Warrens, Matthijs J.
|
|
2015
|
|
1 |
p. 71-84
|
artikel
|
| 4 |
A constrained robust proposal for mixture modeling avoiding spurious solutions
|
García-Escudero, L. A.
|
|
2013
|
|
1 |
p. 27-43
|
artikel
|
| 5 |
A cost-sensitive constrained Lasso
|
Blanquero, Rafael
|
|
|
|
1 |
p. 121-158
|
artikel
|
| 6 |
Adaptive dissimilarity index for measuring time series proximity
|
Chouakria, Ahlame Douzal
|
|
2007
|
|
1 |
p. 5-21
|
artikel
|
| 7 |
Advances in credit scoring: combining performance and interpretation in kernel discriminant analysis
|
Liberati, Caterina
|
|
2015
|
|
1 |
p. 121-138
|
artikel
|
| 8 |
A fragmented-periodogram approach for clustering big data time series
|
Caiado, Jorge
|
|
|
|
1 |
p. 117-146
|
artikel
|
| 9 |
A generalized maximum entropy estimator to simple linear measurement error model with a composite indicator
|
Carpita, Maurizio
|
|
2016
|
|
1 |
p. 139-158
|
artikel
|
| 10 |
A LASSO-penalized BIC for mixture model selection
|
Bhattacharya, Sakyajit
|
|
2013
|
|
1 |
p. 45-61
|
artikel
|
| 11 |
A latent variables approach for clustering mixed binary and continuous variables within a Gaussian mixture model
|
Morlini, Isabella
|
|
2011
|
|
1 |
p. 5-28
|
artikel
|
| 12 |
A multilevel finite mixture item response model to cluster examinees and schools
|
Gnaldi, Michela
|
|
2015
|
|
1 |
p. 53-70
|
artikel
|
| 13 |
Analyzing multiset data by the Power STATIS-ACT method
|
Bénasséni, Jacques
|
|
2011
|
|
1 |
p. 49-65
|
artikel
|
| 14 |
An empirical comparison and characterisation of nine popular clustering methods
|
Hennig, Christian
|
|
|
|
1 |
p. 201-229
|
artikel
|
| 15 |
A novel semi-supervised support vector machine with asymmetric squared loss
|
Pei, Huimin
|
|
|
|
1 |
p. 159-191
|
artikel
|
| 16 |
An update algorithm for restricted random walk clustering for dynamic data sets
|
Franke, Markus
|
|
2009
|
|
1 |
p. 63-92
|
artikel
|
| 17 |
A principal component method to impute missing values for mixed data
|
Audigier, Vincent
|
|
2014
|
|
1 |
p. 5-26
|
artikel
|
| 18 |
A robust spatial autoregressive scalar-on-function regression with t-distribution
|
Huang, Tingting
|
|
|
|
1 |
p. 57-81
|
artikel
|
| 19 |
Assessing similarities between spatial point patterns with a Siamese neural network discriminant model
|
Jalilian, Abdollah
|
|
|
|
1 |
p. 21-42
|
artikel
|
| 20 |
Assessing the asymmetric effects on branch rivalry of Spanish financial sector restructuring
|
Sagarra, Marti
|
|
2014
|
|
1 |
p. 131-153
|
artikel
|
| 21 |
Assessing trimming methodologies for clustering linear regression data
|
Torti, Francesca
|
|
2018
|
|
1 |
p. 227-257
|
artikel
|
| 22 |
A uniform framework for the combination of penalties in generalized structured models
|
Oelker, Margret-Ruth
|
|
2015
|
|
1 |
p. 97-120
|
artikel
|
| 23 |
Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy
|
Corander, Jukka
|
|
2009
|
|
1 |
p. 3-24
|
artikel
|
| 24 |
CenetBiplot: a new proposal of sparse and orthogonal biplots methods by means of elastic net CSVD
|
González-García, Nerea
|
|
|
|
1 |
p. 5-19
|
artikel
|
| 25 |
Claims fraud detection with uncertain labels
|
Vandervorst, Félix
|
|
|
|
1 |
p. 219-243
|
artikel
|
| 26 |
Classification of brain activation via spatial Bayesian variable selection in fMRI regression
|
Kalus, Stefanie
|
|
2013
|
|
1 |
p. 63-83
|
artikel
|
| 27 |
Classification using sequential order statistics
|
Katzur, Alexander
|
|
|
|
1 |
p. 201-230
|
artikel
|
| 28 |
CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal information
|
Vicari, Donatella
|
|
2015
|
|
1 |
p. 43-64
|
artikel
|
| 29 |
Clustering and classification via cluster-weighted factor analyzers
|
Subedi, Sanjeena
|
|
2013
|
|
1 |
p. 5-40
|
artikel
|
| 30 |
Clustering discrete-valued time series
|
Roick, Tyler
|
|
|
|
1 |
p. 209-229
|
artikel
|
| 31 |
Clustering genomic words in human DNA using peaks and trends of distributions
|
Tavares, Ana Helena
|
|
|
|
1 |
p. 57-76
|
artikel
|
| 32 |
Clustering space-time series: FSTAR as a flexible STAR approach
|
Otranto, Edoardo
|
|
2018
|
|
1 |
p. 175-199
|
artikel
|
| 33 |
Clustering via finite nonparametric ICA mixture models
|
Zhu, Xiaotian
|
|
2018
|
|
1 |
p. 65-87
|
artikel
|
| 34 |
Clusterwise elastic-net regression based on a combined information criterion
|
Bry, Xavier
|
|
|
|
1 |
p. 75-107
|
artikel
|
| 35 |
Co-clustering contaminated data: a robust model-based approach
|
Fibbi, Edoardo
|
|
|
|
1 |
p. 121-161
|
artikel
|
| 36 |
Cohen’s linearly weighted kappa is a weighted average
|
Warrens, Matthijs J.
|
|
2011
|
|
1 |
p. 67-79
|
artikel
|
| 37 |
Cohen’s weighted kappa with additive weights
|
Warrens, Matthijs J.
|
|
2013
|
|
1 |
p. 41-55
|
artikel
|
| 38 |
Comparing partitions of two sets of units based on the same variables
|
Youness, Genane
|
|
2009
|
|
1 |
p. 53-64
|
artikel
|
| 39 |
Constrained principal component analysis of standardized data for biplots with unit-length variable vectors
|
Adachi, Kohei
|
|
2010
|
|
1 |
p. 23-36
|
artikel
|
| 40 |
Contamination transformation matrix mixture modeling for skewed data groups with heavy tails and scatter
|
Zhu, Xuwen
|
|
|
|
1 |
p. 85-101
|
artikel
|
| 41 |
Count regression trees
|
Liu, Nan-Ting
|
|
|
|
1 |
p. 5-27
|
artikel
|
| 42 |
Data clustering based on principal curves
|
Moraes, Elson Claudio Correa
|
|
|
|
1 |
p. 77-96
|
artikel
|
| 43 |
Detection of multivariate outliers in business survey data with incomplete information
|
Todorov, Valentin
|
|
2010
|
|
1 |
p. 37-56
|
artikel
|
| 44 |
Dichotomic lattices and local discretization for Galois lattices
|
Girard, Nathalie
|
|
2015
|
|
1 |
p. 49-77
|
artikel
|
| 45 |
Early identification of biliary atresia using subspace and the bootstrap methods
|
Hayashi, Kuniyoshi
|
|
|
|
1 |
p. 163-179
|
artikel
|
| 46 |
Editorial
|
Bock, Hans-Hermann
|
|
2011
|
|
1 |
p. 1-2
|
artikel
|
| 47 |
Editorial
|
Bock, Hans-Hermann
|
|
2012
|
|
1 |
p. 1-2
|
artikel
|
| 48 |
Editorial
|
Vichi, Maurizio
|
|
2012
|
|
1 |
p. 3-4
|
artikel
|
| 49 |
Editorial
|
|
|
2013
|
|
1 |
p. 1-3
|
artikel
|
| 50 |
Editorial
|
Bock, Hans-Hermann
|
|
2008
|
|
1 |
p. 1-2
|
artikel
|
| 51 |
Editorial
|
Bock, Hans-Hermann
|
|
2010
|
|
1 |
p. 1-2
|
artikel
|
| 52 |
Editorial
|
Bock, Hans-Hermann
|
|
2009
|
|
1 |
p. 1-2
|
artikel
|
| 53 |
Editorial
|
Bock, Hans-Hermann
|
|
2007
|
|
1 |
p. 1-3
|
artikel
|
| 54 |
Editorial for ADAC issue 1 of volume 15 (2021)
|
Vichi, Maurizio
|
|
|
|
1 |
p. 1-4
|
artikel
|
| 55 |
Editorial for ADAC issue 1 of volume 16 (2022)
|
Ingrassia, Salvatore
|
|
|
|
1 |
p. 1-3
|
artikel
|
| 56 |
Editorial for ADAC issue 1 of volume 14 (2020)
|
|
|
|
|
1 |
p. 1-4
|
artikel
|
| 57 |
Editorial for ADAC issue 1 of volume 17 (2023)
|
Vichi, Maurizio
|
|
|
|
1 |
p. 1-4
|
artikel
|
| 58 |
Editorial for issue 1/2017
|
|
|
2017
|
|
1 |
p. 1-4
|
artikel
|
| 59 |
Editorial for issue 1/2016
|
|
|
2016
|
|
1 |
p. 1-3
|
artikel
|
| 60 |
Editorial for Special Issue on Analysis of Asymmetric Relationships
|
Bove, Giuseppe
|
|
2018
|
|
1 |
p. 1-4
|
artikel
|
| 61 |
Editorial for Special Issue on Symbolic Data Analysis
|
|
|
2015
|
|
1 |
p. 1-4
|
artikel
|
| 62 |
Efficient regularized spectral data embedding
|
Labiod, Lazhar
|
|
|
|
1 |
p. 99-119
|
artikel
|
| 63 |
Ensemble of optimal trees, random forest and random projection ensemble classification
|
Khan, Zardad
|
|
|
|
1 |
p. 97-116
|
artikel
|
| 64 |
Evaluation of the evolution of relationships between topics over time
|
Gaul, Wolfgang
|
|
2016
|
|
1 |
p. 159-178
|
artikel
|
| 65 |
Exploring incomplete data using visualization techniques
|
Templ, Matthias
|
|
2011
|
|
1 |
p. 29-47
|
artikel
|
| 66 |
Extreme logistic regression
|
Ngufor, Che
|
|
2014
|
|
1 |
p. 27-52
|
artikel
|
| 67 |
Finite mixture biclustering of discrete type multivariate data
|
Fernández, Daniel
|
|
2018
|
|
1 |
p. 117-143
|
artikel
|
| 68 |
Finite mixture of regression models for censored data based on scale mixtures of normal distributions
|
Zeller, Camila Borelli
|
|
2018
|
|
1 |
p. 89-116
|
artikel
|
| 69 |
Finite mixtures, projection pursuit and tensor rank: a triangulation
|
Loperfido, Nicola
|
|
2018
|
|
1 |
p. 145-173
|
artikel
|
| 70 |
Flexible mixture regression with the generalized hyperbolic distribution
|
Kim, Nam-Hwui
|
|
|
|
1 |
p. 33-60
|
artikel
|
| 71 |
From-below Boolean matrix factorization algorithm based on MDL
|
Makhalova, Tatiana
|
|
|
|
1 |
p. 37-56
|
artikel
|
| 72 |
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering
|
Frühwirth-Schnatter, Sylvia
|
|
2018
|
|
1 |
p. 33-64
|
artikel
|
| 73 |
Functional fuzzy clusterwise regression analysis
|
Tan, Tianyu
|
|
2013
|
|
1 |
p. 57-82
|
artikel
|
| 74 |
Galois closed entity sets and k-balls of quasi-ultrametric multi-way dissimilarities
|
Diatta, Jean
|
|
2007
|
|
1 |
p. 53-65
|
artikel
|
| 75 |
Generalized constrained co-inertia analysis
|
Amenta, Pietro
|
|
2008
|
|
1 |
p. 81-105
|
artikel
|
| 76 |
Generalized GIPSCAL re-revisited: a fast convergent algorithm with acceleration by the minimal polynomial extrapolation
|
Loisel, Sébastien
|
|
2011
|
|
1 |
p. 57-75
|
artikel
|
| 77 |
Generalized mixture models, semi-supervised learning, and unknown class inference
|
Frame, Samuel J.
|
|
2007
|
|
1 |
p. 23-38
|
artikel
|
| 78 |
Hierarchical clustering of asymmetric networks
|
Carlsson, Gunnar
|
|
2017
|
|
1 |
p. 65-105
|
artikel
|
| 79 |
How well do SEM algorithms imitate EM algorithms? A non-asymptotic analysis for mixture models
|
Blömer, Johannes
|
|
|
|
1 |
p. 147-173
|
artikel
|
| 80 |
Interpolation of spatial and spatio-temporal Gaussian fields using Gaussian Markov random fields
|
Fontanella, L.
|
|
2008
|
|
1 |
p. 63-79
|
artikel
|
| 81 |
Interval forecasts based on regression trees for streaming data
|
Zhao, Xin
|
|
|
|
1 |
p. 5-36
|
artikel
|
| 82 |
Kappa coefficients for dichotomous-nominal classifications
|
Warrens, Matthijs J.
|
|
|
|
1 |
p. 193-208
|
artikel
|
| 83 |
Kurtosis removal for data pre-processing
|
Loperfido, Nicola
|
|
|
|
1 |
p. 239-267
|
artikel
|
| 84 |
Lasso-constrained regression analysis for interval-valued data
|
Giordani, Paolo
|
|
2014
|
|
1 |
p. 5-19
|
artikel
|
| 85 |
Latent class CUB models
|
Grilli, Leonardo
|
|
2013
|
|
1 |
p. 105-119
|
artikel
|
| 86 |
Learning a metric when clustering data points in the presence of constraints
|
Abin, Ahmad Ali
|
|
|
|
1 |
p. 29-56
|
artikel
|
| 87 |
Least squares estimation of linear regression models for convex compact random sets
|
González-Rodríguez, Gil
|
|
2007
|
|
1 |
p. 67-81
|
artikel
|
| 88 |
Linear regression for numeric symbolic variables: a least squares approach based on Wasserstein Distance
|
Irpino, Antonio
|
|
2015
|
|
1 |
p. 81-106
|
artikel
|
| 89 |
Methods for merging Gaussian mixture components
|
Hennig, Christian
|
|
2010
|
|
1 |
p. 3-34
|
artikel
|
| 90 |
Methods for the analysis of asymmetric pairwise relationships
|
Bove, Giuseppe
|
|
2018
|
|
1 |
p. 5-31
|
artikel
|
| 91 |
Minimum adjusted Rand index for two clusterings of a given size
|
Chacón, José E.
|
|
|
|
1 |
p. 125-133
|
artikel
|
| 92 |
Minimum Class Variance SVM+ for data classification
|
Zhu, Wenxin
|
|
2015
|
|
1 |
p. 79-96
|
artikel
|
| 93 |
Mixed Deep Gaussian Mixture Model: a clustering model for mixed datasets
|
Fuchs, Robin
|
|
|
|
1 |
p. 31-53
|
artikel
|
| 94 |
Mixture-model-based signal denoising
|
Samé, Allou
|
|
2007
|
|
1 |
p. 39-51
|
artikel
|
| 95 |
Mixture modeling with normalizing flows for spherical density estimation
|
Ng, Tin Lok James
|
|
|
|
1 |
p. 103-120
|
artikel
|
| 96 |
Mixtures of biased sentiment analysers
|
Salter-Townshend, Michael
|
|
2013
|
|
1 |
p. 85-103
|
artikel
|
| 97 |
Model-based clustering and outlier detection with missing data
|
Tong, Hung
|
|
|
|
1 |
p. 5-30
|
artikel
|
| 98 |
Model-based clustering using a new multivariate skew distribution
|
Tomarchio, Salvatore D.
|
|
|
|
1 |
p. 61-83
|
artikel
|
| 99 |
Modeling and forecasting interval time series with threshold models
|
Rodrigues, Paulo M. M.
|
|
2014
|
|
1 |
p. 41-57
|
artikel
|
| 100 |
Multiple straight-line fitting using a Bayes factor
|
Lara-Alvarez, Carlos
|
|
2016
|
|
1 |
p. 205-218
|
artikel
|
| 101 |
Multivariate cluster weighted models using skewed distributions
|
Gallaugher, Michael P. B.
|
|
|
|
1 |
p. 93-124
|
artikel
|
| 102 |
NMF versus ICA for blind source separation
|
Mirzal, Andri
|
|
2014
|
|
1 |
p. 25-48
|
artikel
|
| 103 |
Notes on the H-measure of classifier performance
|
Hand, D. J.
|
|
|
|
1 |
p. 109-124
|
artikel
|
| 104 |
On visual distances for spectrum-type functional data
|
Cholaquidis, A.
|
|
2015
|
|
1 |
p. 5-24
|
artikel
|
| 105 |
Optimal arrangements of hyperplanes for SVM-based multiclass classification
|
Blanco, Víctor
|
|
|
|
1 |
p. 175-199
|
artikel
|
| 106 |
Optimal projections for Gaussian discriminants
|
Hofmeyr, David P.
|
|
|
|
1 |
p. 43-73
|
artikel
|
| 107 |
Optimum simultaneous discretization with data grid models in supervised classification: a Bayesian model selection approach
|
Boullé, Marc
|
|
2009
|
|
1 |
p. 39-61
|
artikel
|
| 108 |
Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study
|
Ullmann, Theresa
|
|
|
|
1 |
p. 211-238
|
artikel
|
| 109 |
Plastic card fraud detection using peer group analysis
|
Weston, David J.
|
|
2008
|
|
1 |
p. 45-62
|
artikel
|
| 110 |
Poisson degree corrected dynamic stochastic block model
|
Riverain, Paul
|
|
|
|
1 |
p. 135-162
|
artikel
|
| 111 |
Principal component analysis for probabilistic symbolic data: a more generic and accurate algorithm
|
Chen, Meiling
|
|
2014
|
|
1 |
p. 59-79
|
artikel
|
| 112 |
Random effects clustering in multilevel modeling: choosing a proper partition
|
Conversano, Claudio
|
|
2018
|
|
1 |
p. 279-301
|
artikel
|
| 113 |
Random walk distances in data clustering and applications
|
Liu, Sijia
|
|
2013
|
|
1 |
p. 83-108
|
artikel
|
| 114 |
Regularized fuzzy clusterwise ridge regression
|
Suk, Hye Won
|
|
2009
|
|
1 |
p. 35-51
|
artikel
|
| 115 |
Regularized logistic discrimination with basis expansions for the early detection of Alzheimer’s disease based on three-dimensional MRI data
|
Araki, Yuko
|
|
2013
|
|
1 |
p. 109-119
|
artikel
|
| 116 |
Relating brand confusion to ad similarities and brand strengths through image data analysis and classification
|
Baier, Daniel
|
|
2017
|
|
1 |
p. 155-171
|
artikel
|
| 117 |
Robust clustering around regression lines with high density regions
|
Cerioli, Andrea
|
|
2013
|
|
1 |
p. 5-26
|
artikel
|
| 118 |
Robust clustering for functional data based on trimming and constraints
|
Rivera-García, Diego
|
|
2018
|
|
1 |
p. 201-225
|
artikel
|
| 119 |
Robust clustering of functional directional data
|
Álvarez-Esteban, Pedro C.
|
|
|
|
1 |
p. 181-199
|
artikel
|
| 120 |
Robust estimation of efficient mean–variance frontiers
|
Grossi, Luigi
|
|
2011
|
|
1 |
p. 3-22
|
artikel
|
| 121 |
Robust mixture regression modeling based on two-piece scale mixtures of normal distributions
|
Zarei, Atefeh
|
|
|
|
1 |
p. 181-210
|
artikel
|
| 122 |
Robust optimal classification trees under noisy labels
|
Blanco, Victor
|
|
|
|
1 |
p. 155-179
|
artikel
|
| 123 |
sARI: a soft agreement measure for class partitions incorporating assignment probabilities
|
Flynt, Abby
|
|
2018
|
|
1 |
p. 303-323
|
artikel
|
| 124 |
Semiparametric mixture of linear regressions with nonparametric Gaussian scale mixture errors
|
Oh, Sangkon
|
|
|
|
1 |
p. 5-31
|
artikel
|
| 125 |
Simultaneous dimension reduction and clustering via the NMF-EM algorithm
|
Carel, Léna
|
|
|
|
1 |
p. 231-260
|
artikel
|
| 126 |
Skew symmetry in retrospect
|
Gower, John C.
|
|
2014
|
|
1 |
p. 33-41
|
artikel
|
| 127 |
Sparsifying the least-squares approach to PCA: comparison of lasso and cardinality constraint
|
Guerra-Urzola, Rosember
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Supervised box clustering
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Supervised clustering of variables
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The $$k$$k-means algorithm for 3D shapes with an application to apparel design
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The role of diversity and ensemble learning in credit card fraud detection
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Where are the large and difficult datasets?
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