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ADAC Editorial Issue 2 2009
No full textThis issue no. 2 of volume 3(2009) of the journal Advances in Data Analysis and
Classification (ADAC) contains four articles that deal with the usage of string distance
in phylogeny, with the selection of variables in model-based clustering, with clustering
under the presence of outlying observations, and with Robinsonian dissimilaritie
Editorial Issue 2/2012
No full textThis second issue of volume 6 (2012) of the journal Advances in Data Analysis
and Classification (ADAC) comprises four articles which deal with dissimilarity and
similarity measures for comparing dendrograms, robust clustering, orthogonal rotation
in a principal component method for a mixture of qualitative and quantitative variables,
and the symbolic analysis of histogram data by means of a modified interval principal
component analysis (PCA). Proposed methods are usually illustrated by real-case or
simulated example
Editorial Issue 2/2014
No full textThe second issue of volume 8 (2014) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: a comparison of various information criteria used to select the number of latent states of a multivariate latent Markov model; a new methodology for visualizing, on a dimension reduced subspace, the classification structure and the geometric characteristics of an estimated Gaussian mixture model in discriminant analysis; parameter estimation for model-based clustering in the case of a finite mixture of normal inverse Gaussian (NIG) distributions; a discrimination approach for separating, in gamma-ray astronomy, the gamma-ray signal from a hadronic background; finally, a new simple majorization–minimization (MM) algorithm to solve certain types of optimization problems in multivariate analysis, e.g., a common principal components model for G
groups proposed by Flury. The proposed methods are illustrated by real-case or simulated examples
Editorial for issue 3/2017
No full textThe present issue 3 of volume 11 (2017) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: robust classifiers for multivariate and functional data, constrained clustering, fuzzy neural clustering network, density based trajectory clustering, flower pollination search algorithm, algorithm to identify the prior probabilities for classification problem and general location model
ADAC Editorial Issue 3 2008
No full textThe first part of this issue of the journal ‘Advances in Data Analysis and Classification’
is designed as a Special Issue on
Optimisation and Non-Convex Programming in Data Mining.
It has been organized by the Guest Editors An Hoai LE THI (Metz/France), Tao
PHAM DINH (Rouen/France), and Gunter RITTER (Passau/Germany). It comprizes
four papers that are summarized below in the preface of the Guest Editors. It is followed
by a Part II consists in two contributed papers from the field of data analysis and
classification
Editorial for issue 2/2018
No full textThe present issue 2 of volume 12 (2018) of the journal Advances in Data Analysis and Classification (ADAC) includes 10 articles which deal with: Gaussian and non-Gaussian mixture modeling, selection of ‘reasonable’ and non-degenerate cluster solutions, clustering imbalanced and high-dimensional data, clusterwise multiblock analysis, linear discrimination for supervised versus partially supervised data, learning of a distance metric, clustering of shapes by currents, a semiparametric Bayesian model for hospital evaluation, and estimation of a precision matrix
Editorial for issue 3/2019
No full textThis is the Editorial of the Issue 3 of 2019. Several papers have been discusse
Editorial ADAC issue 3, volume 10 (2016)
No full textThis third issue of volume 10 (2016) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: supervised box-based classification; supervised classification using stratified graphical models; semi-supervised classification with constraints; outlier detection for time series data; quantile regression for binary response data; and clustering time series
Editorial 4/2014
No full textThis fourth issue of volume 8 (2014) of the journal Advances in Data Analysis and Classification (ADAC) includes four articles which are mainly devoted to the analysis of real-case data: a new methodology for clustering financial time series; a feature selection algorithm for classification in the problem of fault diagnosis; a comparison of five recursive partitioning methods to find person subgroups involved in meaningful treatment-subgroup interactions, and a latent class approach for analyzing the attitudes of Polish people on the adoption of the Euro
Editorial for issue 2/2015
No full textThis second issue of volume 9 (2019) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: the correspondence analysis on a generalized aggregated lexical table (CA-GALT); new univariate and bivariate statistics for distributional variables in the framework of symbolic data analysis; the selection of a number of clusters that not only fits well the data, but simultaneously uses the potential illustrative ability of the available external variables in the model-based clustering context; a mixture model averaging for clustering; a simple nonlinear biplot that represents the marker points of a variable on a curved line that is governed by splines
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