International Journal of Computational Intelligence Systems

Volume 11, Issue 1, January 2018, Pages 282 - 295

A locally weighted learning method based on a data gravitation model for multi-target regression

Authors
Oscar Reyes1, Alberto Cano2, Habib M. Fardoun3, Sebastián Ventura1, 3
1 Department of Computer Science and Numerical Analysis, University of Córdoba, Córdoba, Spain
2 Department of Computer Science, Virginia Commonwealth University, United States
3 Department of Information Systems, King Abdulaziz University, Saudi Arabia Kingdom
Received 13 July 2017, Accepted 5 October 2017, Available Online 1 January 2018.
DOI
https://doi.org/10.2991/ijcis.11.1.22How to use a DOI?
Keywords
Multi-Target Regression, Locally Weighted Regression, Data Gravitation Approach
Abstract

Locally weighted regression allows to adjust the regression models to nearby data of a query example. In this paper, a locally weighted regression method for the multi-target regression problem is proposed. A novel way of weighting data based on a data gravitation-based approach is presented. The process of weighting data does not need to decompose the multi-target data into several single-target problems. This weighted regression method can be used with any multi-target regressor as a local method to provide the target vector of a query example. The proposed method was assessed on the largest collection of multi-target regression datasets publicly available. The experimental stage showed that the performance of multi-target regressors can be significantly improved by means of fitting the models to local training data.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
282 - 295
Publication Date
2018/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.11.1.22How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Oscar Reyes
AU  - Alberto Cano
AU  - Habib M. Fardoun
AU  - Sebastián Ventura
PY  - 2018
DA  - 2018/01
TI  - A locally weighted learning method based on a data gravitation model for multi-target regression
JO  - International Journal of Computational Intelligence Systems
SP  - 282
EP  - 295
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.22
DO  - https://doi.org/10.2991/ijcis.11.1.22
ID  - Reyes2018
ER  -