3 papers
stat.ML2024
Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features
Fabrizio Maturo, Annamaria Porreca
The positioning of this research falls within the scalar-on-function classification literature, a field of significant interest across various domains, particularly in statistics,…
stat.ML2024
Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations
Fabrizio Maturo, Annamaria Porreca
This paper introduces a novel supervised classification strategy that integrates functional data analysis (FDA) with tree-based methods, addressing the challenges of high-dimension…
stat.ML2024
Demystifying Functional Random Forests: Novel Explainability Tools for Model Transparency in High-Dimensional Spaces
Fabrizio Maturo, Annamaria Porreca
The advent of big data has raised significant challenges in analysing high-dimensional datasets across various domains such as medicine, ecology, and economics. Functional Data Ana…