A robust method for linear regression of symbolic interval data

作者：Domingues Marco A O; de Souza Renata M C R^*; Cysneiros Francisco Jose A

来源：Pattern Recognition Letters, 2010, 31(13): 1991-1996.

DOI：10.1016/j.patrec.2010.06.008

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

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.

• 出版日期2010-10-1