Khaled M. S. Badran

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In this paper we investigate using multi-objective genetic programming to evolve a feature extraction stage for multiple-class classifiers. We find mappings which transform the input space into a new, multi-dimensional decision space to increase the discrimination between all classes; the number of dimensions of this decision space is optimized as part of(More)
It has been observed previously that genetic programming populations can collapse to all single node trees when a parsimony measure (tree node count) is used in a multiobjective setting. We have investigated the circumstances under which this can occur for both the 6-parity boolean learning task and a range of benchmark machine learning problems. We(More)
Using multiobjective genetic programming with a complexity objective to overcome tree bloat is usually very successful but can sometimes lead to undesirable collapse of the population to all single-node trees. In this paper we report a detailed examination of why and when collapse occurs. We have used different types of crossover and mutation operators(More)
This paper introduces a Web Recommendation Framework based on the usage history to be applied for Site Modification as one of the applications of Web Usage Mining (WUM) that is applicable for online business and marketing applications. The framework focuses on the three main interdependent tasks for performing WUM which are Preprocessing, Pattern Discovery(More)
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