44 research outputs found
Regression Error Characteristic Optimisation of Non-Linear Models.
Get PDFCopyright © 2006 Springer-Verlag Berlin Heidelberg. The final publication is available at link.springer.comBook title: Multi-Objective Machine LearningIn 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
Developmental Reaction Norms: the Interactions among Allometry, Ontogeny and Plasticity
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Evolution of carboxylating enzymes involved in paramylon synthesis (phosphoenolpyruvate carboxylase and carboxykinase) in heterotrophically grown Euglena gracilis
No full textDesign of Experiments in Computational Intelligence: On the Use of Statistical Inference
No full textEffects of Two Different Dynamic Environments on Force Adaptation: Exposure to a New Force but Not the Preceding Force Experience Accounts for Transition- and After-Effects
No full textAccountability Online: Understanding the Web-Based Accountability Practices of Nonprofit Organizations
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