Support Vector Regression for imprecise data

In this work, a regression problem is studied where the elements of the database are sets with certain geometrical properties. In particular, our model can be applied to handle data affected by some kind of noise or uncertainty and interval-valued data, and databases with missing values as well. The proposed formulation is based on the standard epsilon-Support Vector Regression approach. In the interval-data case, two different formulations will be obtained, according to the way of measuring the distance between the prediction and the actual intervals. Computational experiments with real databases are performed.


Technical Report MOSI/35, MOSI Department, Vrije Universiteit Brussel, October 2007



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