This paper presents a tool for web usage mining. The aim is centered on providing a tool that facilitates the mining process rather than implement elaborated algorithms and techniq...
Abstract. The importance of modularity in product innovation is analyzed in this paper. Through simulations with an agent-based modular economic model, we examine the significance...
This work presents a research on the performance capabilities of an extension of the ViSOM (Visualization Induced SOM) algorithm by the use of the ensemble meta-algorithm and a lat...
Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
Clustering is used to generate groupings of data from a large dataset, with the intention of representing the behavior of a system as accurately as possible. In this sense, cluster...
There are lots of validation indexes and techniques to study clustering results. Biclustering algorithms have been applied in Systems Biology, principally in DNA Microarray analysi...
The dependence of the classification error on the size of a bagging ensemble can be modeled within the framework of Monte Carlo theory for ensemble learning. These error curves ar...
We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. T...