Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
Abstract. Genetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. Hence, incorporating mechanisms used in nature may improve the perform...
A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated a...
In this contribution, a way to enhance the performance of the classic Genetic Algorithm is proposed. The idea of restarting a Genetic Algorithm is applied in order to obtain better...
Grigorios N. Beligiannis, Georgios A. Tsirogiannis...
Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups h...
—In this research, the Genetic Algorithm (GA) and Space-Filling Curve (SFC) are combined along with the use of Taguchi method for finding the optimal combination of parameters. T...
In this paper, we highlight the use of synthetic data sets to analyze learners behavior under bounded complexity. We propose a method to generate synthetic data sets with a specif...
Abstract--We present an approach to compress arbitrary files using a Huffman-like prefix-free code generated through the use of a genetic algorithm, thus requiring no prior knowled...
- Besides the difficulty of the application problem to be solved with Genetic Algorithms (GAs), an additional difficulty arises because the quality of the solution found, or the ...
Learning texts contain much implicit knowledge which is ideally presented to the learner in a structured manner - a typical example being definitions of terms in the text, which w...