While learning ensembles have been widely used for various pattern recognition tasks, surprisingly, they have found limited application in problems related to medical image analysi...
Anant Madabhushi, Jianbo Shi, Michael D. Feldman, ...
A method for tuning MLP learning parameters in an ensemble classifier framework is presented. No validation set or cross-validation technique is required to optimize parameters for...
Since accurate classification of DNA microarray is a very important issue for the treatment of cancer, it is more desirable to make a decision by combining the results of various ...
This paper presents an investigation into exploiting the population-based nature of Learning Classifier Systems for their use within highly-parallel systems. In particular, the use...
Larry Bull, Matthew Studley, Anthony J. Bagnall, I...
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...