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ECML
2007
Springer

Multi-objective Genetic Programming for Multiple Instance Learning

14 years 6 months ago
Multi-objective Genetic Programming for Multiple Instance Learning
Abstract. This paper introduces the use of multi-objective evolutionary algorithms in multiple instance learning. In order to achieve this purpose, a multi-objective grammar-guided genetic programming algorithm (MOG3P-MI) has been designed. This algorithm has been evaluated and compared to other existing multiple instance learning algorithms. Research on the performance of our algorithm is carried out on two wellknown drug activity prediction problems, Musk and Mutagenesis, both problems being considered typical benchmarks in multiple instance problems. Computational experiments indicate that the application of the MOG3P-MI algorithm improves accuracy and decreases computational cost with respect to other techniques.
Amelia Zafra, Sebastián Ventura
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where ECML
Authors Amelia Zafra, Sebastián Ventura
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