A robust method for linear regression of symbolic interval data

被引：47

作者：

Domingues, Marco A. O. ^{[1
]}

de Souza, Renata M. C. R. ^{[1
]}

Cysneiros, Francisco Jose A. ^{[2
]}

机构：

[1] Univ Fed Pernambuco, Ctr Informat, BR-50740540 Recife, PE, Brazil

[2] Univ Fed Pernambuco, Dept Estat, CCEN, BR-50740540 Recife, PE, Brazil

来源：

PATTERN RECOGNITION LETTERS | 2010年 / 31卷 / 13期

关键词：

Symbolic interval-valued data; Symbolic data analysis; Symmetrical linear regression; Outliers;

D O I：

10.1016/j.patrec.2010.06.008

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a new linear regression method for interval valued-data. The method is based on the symmetrical linear regression methodology such that the prediction of the lower and upper bounds of the interval value of the dependent variable is not damaged by the presence of interval-valued data out-liers. The method considers mid-points and ranges of the interval values assumed by the variables in the learning set. The prediction of the boundaries of an interval is accomplished through a combination of predictions from mid-point and range of the interval values. The evaluation of the method is based on the average behavior of a pooled root mean-square error. Experiments with real and simulated symbolic interval data sets demonstrate the usefulness of this symbolic symmetrical linear regression method. (c) 2010 Elsevier B.V. All rights reserved.

引用

页码：1991 / 1996

页数：6

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