Functional feature selection by weighted projections in pathological voice detection

Luis Sánchez Giraldo, Fernando Martínez Tabares, Germán Castellanos Domínguez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


In this paper, we introduce an adaptation of a multivariate feature selection method to deal with functional features. In our case, observations are described by a set of functions defined over a common domain (e.g. a time interval). The feature selection method consists on combining variable weighting with a feature extraction projection. Although the employed method was primarily intended for observations described by vectors in ℝn, we propose a simple extension that allows us to select a set of functional features, which is well suited for classification. This study is complemented by the incorporation of Functional Principal Component Analysis (FPCA) that project functions into a finite dimensional space were we can perform classification easily. Another remarkable property of FPCA is that it can provide insight about the nature of the functional features. The proposed algorithms are tested on a pathological voice detection task. Two databases are considered: Massachusetts Eye and Ear Infirmary Voice Laboratory voice disorders database and Universidad Politécnica de Madrid voice database. As a result, we obtain a canonical function whose time average is enough to reach similar performances to the ones reported in the literature.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision and Applications - 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Proceedings
Number of pages8
StatePublished - 2009
Event14th Iberoamerican Conference on Pattern Recognition, CIARP 2009 - Guadalajara, Jalisco, Mexico
Duration: Nov 15 2009Nov 18 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5856 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th Iberoamerican Conference on Pattern Recognition, CIARP 2009
CityGuadalajara, Jalisco

Bibliographical note

Funding Information:
This is part of the project 20201004208, funded by Universidad Nacional de Colombia.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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