Adressing Remitting Behavior Using an Ordinal Classification Approach

Áreas de investigación:

• Methodology - Machine learning

Año:

2013

Tipo de publicación:

Artículo en conferencia

Autores:

• Campoy-Muñoz, Pilar
• Gutiérrez, Pedro Antonio
• Hervás-Martínez, César

Editor:

José Manuel Ferrández Vicente, José Ramón Álvarez Sánchez, Félix de la Paz López and Fco. Javier Toledo Moreo

Volumen:

7931

Título del libro:

Natural and Artificial Computation in Engineering and Medical Applications (5th International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC 2013), Part II)

Serie:

Lecture Notes in Computer Science

Páginas:

326-335

Dirección:

Mallorca, Spain

Organización:

Mallorca, Spain

Mes:

10th-14th June

ISBN:

978-3-642-38621-3

ISSN:

0302-9743

BibTex:

@conference{IWINACPilar2013, author = "Pilar Campoy-Mu{\~n}oz and Pedro Antonio Guti{\'e}rrez and C{\'e}sar Herv{\'a}s-Mart{\'i}nez", abstract = "Remittance flows have drawn the attention of international development community interested in enhancing their potential benefits in the recipient communities. This papers deals with the migrants’ remitting patterns, addressing this economic behavior by a classification approach rather than the traditional regression one. Five nominal and two ordinal classifiers were compared in order to verify the nature of the problem and to obtain a model which predicts the remittance levels sent by migrants according to their individual characteristics. The best performance was achieved by the support vector machine with ordered partitions, an ordinal classifier based on binary decomposition, and thus three remitting profiles for immigrants were drawn from the support vectors obtained. As result, the proposed model can be used as a tool for better factoring remittances flows into the design of policies and programs in the migrants’ home country.", address = "Mallorca, Spain", booktitle = "Natural and Artificial Computation in Engineering and Medical Applications (5th International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC 2013), Part II)", doi = "10.1007/978-3-642-38622-0_34", editor = "Jos{\'e} Manuel Ferr{\'a}ndez Vicente, Jos{\'e} Ram{\'o}n {\'A}lvarez S{\'a}nchez, F{\'e}lix de la Paz L{\'o}pez and Fco. Javier Toledo Moreo", isbn = "978-3-642-38621-3", issn = "0302-9743", month = "10th-14th June", organization = "Mallorca, Spain", pages = "326--335", publisher = "Springer Berlin Heidelberg", series = "Lecture Notes in Computer Science", title = "{A}dressing {R}emitting {B}ehavior {U}sing an {O}rdinal {C}lassification {A}pproach", url = "http://link.springer.com/chapter/10.1007%2F978-3-642-38622-0_34", volume = "7931", year = "2013", }

Abstract:

Remittance flows have drawn the attention of international development community interested in enhancing their potential benefits in the recipient communities. This papers deals with the migrants’ remitting patterns, addressing this economic behavior by a classification approach rather than the traditional regression one. Five nominal and two ordinal classifiers were compared in order to verify the nature of the problem and to obtain a model which predicts the remittance levels sent by migrants according to their individual characteristics. The best performance was achieved by the support vector machine with ordered partitions, an ordinal classifier based on binary decomposition, and thus three remitting profiles for immigrants were drawn from the support vectors obtained. As result, the proposed model can be used as a tool for better factoring remittances flows into the design of policies and programs in the migrants’ home country.