ON THE PREDICTIVE PROPERTIES OF BINARY LINK FUNCTIONS

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

Communications Faculty of Sciences University Ankara Series A1 Mathematics and Statistics
Volume:66 Issue:1
ON THE PREDICTIVE PROPERTIES OF BINARY LINK FUNCTIONS

ON THE PREDICTIVE PROPERTIES OF BINARY LINK FUNCTIONS

Authors : Necla GÜNDÜZ, Ernest FOKOUÉ

Pages : 1-18

Doi:10.1501/Commua1_0000000770

View : 44 | Download : 18

Publication Date : 2017-02-01

Article Type : Research Paper

Abstract :This paper provides a theoretical and computational justification of the long held claim of the similarity of the probit and logit link functions often used in binary classification. Despite this widespread recognition of the strong similarities between these two link functions, very few insert ignore into journalissuearticles values(if any); researchers have dedicated time to carry out a formal study aimed at establishing and characterizing Örmly all the aspects of the similarities and diffierences. This paper proposes a definition of both structural and predictive equivalence of link functions-based binary regression models, and explores the various ways in which they are either similar or dissimilar. From a predictive analytics perspective, it turns out that not only are probit and logit perfectly predictively concordant, but the other link functions like cauchit and complementary log log enjoy very high percentage of predictive equivalence. Throughout this paper, simulated and real life examples demonstrate all the equivalence results that we prove theoretically
Keywords :

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.