Advertisement
Published in:
2006 | OriginalPaper | Chapter
Regression Error Characteristic Optimisation of Non-Linear Models
Author : Jonathan E. Fieldsend
Published in: Multi-Objective Machine Learning
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In this chapter recent research in the area of multi-objective optimisation of regression models is presented and combined. Evolutionary multi-objective optimisation techniques are described for training a population of regression models to optimise the recently defined Regression Error Characteristic Curves (REC). A method which meaningfully compares across regressors and against benchmark models (i.e. ‘random walk’ and maximum a
posteriori
approaches) for varying error rates. Through bootstrapping training data, degrees of confident out-performance are also highlighted.