International Journal of Computational Intelligence Systems

<Previous Article In Issue
Next Article In Issue>
Volume 11, Issue 1, 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
1Department of Computer Science and Numerical Analysis, University of Córdoba, Córdoba, Spain
2Department of Computer Science, Virginia Commonwealth University, United States
3Department of Information Systems, King Abdulaziz University, Saudi Arabia Kingdom
Received 13 July 2017, Accepted 5 October 2017, Available Online 1 January 2018.
DOI
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)

<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
282 - 295
Publication Date
2018/01/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
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

risenwbib
TY  - JOUR
AU  - Oscar Reyes
AU  - Alberto Cano
AU  - Habib M. Fardoun
AU  - Sebastián Ventura
PY  - 2018
DA  - 2018/01/01
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  - 10.2991/ijcis.11.1.22
ID  - Reyes2018
ER  -