3 papers
stat.ML2025
Enhancing Visual Interpretability and Explainability in Functional Survival Trees and Forests
Giuseppe Loffredo, Elvira Romano, Fabrizio MAturo
Functional survival models are key tools for analyzing time-to-event data with complex predictors, such as functional or high-dimensional inputs. Despite their predictive strength,…
stat.ML2024
Randomized Spline Trees for Functional Data Classification: Theory and Application to Environmental Time Series
Donato Riccio, Fabrizio Maturo, Elvira Romano
Functional data analysis (FDA) and ensemble learning can be powerful tools for analyzing complex environmental time series. Recent literature has highlighted the key role of divers…
stat.ME2024
Random Survival Forest for Censored Functional Data
Elvira Romano, Giuseppe Loffredo, Fabrizio Maturo
This paper introduces a Random Survival Forest (RSF) method for functional data. The focus is specifically on defining a new functional data structure, the Censored Functional Data…