2 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
On the classification problem for Poisson Point Processes
Alejandro Cholaquidis, Liliana Forzani, Pamela Llop +1
We study the binary classification problem for Poisson point processes, which are allowed to take values in a general metric space. The problem is tackled in two different ways: es…
Supervised dimension reduction for ordinal predictors
Liliana Forzani, Rodrigo García Arancibia, Pamela Llop +1
In applications involving ordinal predictors, common approaches to reduce dimensionality are either extensions of unsupervised techniques such as principal component analysis, or v…
A nonlinear aggregation type classifier
Alejandro Cholaquidis, Ricardo Fraiman, Juan Kalemkerian +1
We introduce a nonlinear aggregation type classifier for functional data defined on a separable and complete metric space. The new rule is built up from a collection of arbitra…