161 citations · 280 across the 5 of their papers we have counts for
7 papers
ClustGeo: an R package for hierarchical clustering with spatial constraints
Marie Chavent, Vanessa Kuentz-Simonet, Amaury Labenne +1
In this paper, we propose a Ward-like hierarchical clustering algorithm including spatial/geographical constraints. Two dissimilarity matrices and are inputted, along w…
Optimal Projected Variance Group-Sparse Block PCA
Marie Chavent, Guy Chavent
We address the problem of defining a group sparse formulation for Principal Components Analysis (PCA) - or its equivalent formulations as Low Rank approximation or Dictionary Learn…
Combining clustering of variables and feature selection using random forests
Marie Chavent, Robin Genuer, Jerome Saracco
Standard approaches to tackle high-dimensional supervised classification problem often include variable selection and dimension reduction procedures. The novel methodology proposed…
Multivariate Analysis of Mixed Data: The R Package PCAmixdata
Marie Chavent, Vanessa Kuentz-Simonet, Amaury Labenne +1
Mixed data arise when observations are described by a mixture of numerical and categorical variables. The R package PCAmixdata extends to this type of data standard multivariate an…
Orthogonal rotation in PCAMIX
M. Chavent, K. Vanessa, J. Saracco
Kiers (1991) considered the orthogonal rotation in PCAMIX, a principal component method for a mixture of qualitative and quantitative variables. PCAMIX includes the ordinary princi…
ClustOfVar: An R Package for the Clustering of Variables
M. Chavent, V. Kuentz, B. Liquet +1
Clustering of variables is as a way to arrange variables into homogeneous clusters, i.e., groups of variables which are strongly related to each other and thus bring the same infor…
On central tendency and dispersion measures for intervals and hypercubes
Marie Chavent, Jérôme Saracco
The uncertainty or the variability of the data may be treated by considering, rather than a single value for each data, the interval of values in which it may fall. This paper stud…