Generalized Gini linear and quadratic discriminant analyses

Charles Condevaux, Stéphane Mussard, Téa Ouraga and Guillaume Zambrano
Additional contact information
Charles Condevaux: UNIV. NIMES CHROME
Téa Ouraga: UNIV. NIMES CHROME
Guillaume Zambrano: UNIV. NIMES CHROME

METRON, 2020, vol. 78, issue 2, No 8, 219-236

Abstract: Abstract In this paper, a linear discriminant analysis (LDA) is performed in the Gini sense (GDA). Maximizing the generalized Gini gross between-group matrix allows the data to be projected onto discriminant axes. Different methods are investigated, the geometrical approach—based on a particular distance—and the probabilistic approach, which consists in employing the generalized Gini within-group matrix in order to compute the conditional probability of ranking observations in specific groups. Tests based on U-statistics are proposed in order to test for discriminant variables instead of using the well-known Student test that requires homoskedasticity. Monte Carlo simulations show the robustness and the superiority of the GDA on contaminated data compared with various linear classifiers such as logit, SVM and LDA.

Keywords: Classification; Discriminant analysis; Gini (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s40300-020-00178-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metron:v:78:y:2020:i:2:d:10.1007_s40300-020-00178-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40300

DOI: 10.1007/s40300-020-00178-2

Access Statistics for this article

METRON is currently edited by Marco Alfo'

More articles in METRON from Springer, Sapienza Università di Roma
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().