期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (1)
Families of mixtures of multivariate power exponential (MPE) distributions have already been introduced and shown to be competitive for cluster analys......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (3)
Recent work on dissimilarity-based hierarchical clustering has led to the introduction of global objective functions for this classical problem. Sever......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
This study develops a new clustering method for high-dimensional zero-inflated time series data. The proposed method is based on thick-pen transform (......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
A novel clustering model, CPclus, for three-way data concerning a set of objects on which variables are measured by different subjects is proposed. Th......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (3)
In the era of big data, many sparse linear discriminant analysis methods have been proposed for classification and variable selection of the high-dime......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (1)
Imbalanced learning problems typically consist of data with skewed class distributions, coupled with large misclassification costs for the rare events......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
From n-size samples of k-variate points, we construct n x n distance-matrices based on the widely used Euclidean, Manhattan and Hausdorff coefficients......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
In this paper, we present E-ReMI, a new method for studying two-way interaction in row by column (i.e., two-mode) data. E-ReMI is based on a probabili......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (1)
This work studies the problem of clustering one-dimensional data points such that they are evenly distributed over a given number of low variance clus......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
In data, analysis clustering plays a major role. In the past decade varieties of clustering algorithms are proposed and produced better results. But m......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
In generalized linear models (GLMs), measures of lack of fit are typically defined as the deviance between two nested models, and a deviance-based R-2......
期刊： JOURNAL OF CLASSIFICATION, 2023; 40 (2)
The finite mixtures approach identifies homogeneous groups within the sample. The data are aggregated into classes sharing similar patterns without an......
期刊： JOURNAL OF CLASSIFICATION, 2023; ()
Two families of matrix-variate hidden Markov regression models (MV-HMRMs) are here introduced. The distinction between them relies on the role of the ......
