Eugenio Fernández

Hybrid Classifiers for Financial Multicriteria Decision Making: TheCase of Bankruptcy Prediction

This paper compares the accuracy of parametric and nonparametric classifiers on the problem of predicting Bankruptcy. Among the single classifiers, an artificial neural network is found to provide the best results. Two ways of combining classifiers are considered and an additive aggregation method is proposed. We show that both ways of combining produce classifiers whose forecasts are more accurate than the ones obtained with any single model. We suggest that an optimal system for risk rating should combine two or more different techniques.

Bankruptcy Prediction with Artificial Neural Networks

In this paper we compare the forecasting accuracy of feedforward neural networks against various competing models (C4.5, MARS, Discriminant Analysis and Logit) on the problem of predicting bankruptcy. The neural network model is found to provide generally better results, though the computational effort is several orders of magnitude higher. We also consider mixtures of the methods and show that many of these are always more accurate than any single method. We suggest that an optimal system for risk rating should include two or more of the models considered.

Participatory budget formation through the web

We describe a web-based system to support groups in elaborating participatory budgets. Rather than using physical meetings with voting mechanisms, we promote virtual meetings with explicit preference elicitation, guided negotiations and, only if consensus is not reached, voting.

LOMOLEHEA: learning object model for online learning based on the european higher education area

The European Higher Education Area (EHEA), currently under implementation, has forced universities to gradually change all their processes, both teaching and administrative. This has had a great impact on the associated technologies that support those processes. Therefore, the design and definition of all processes related to teaching online must be reviewed, and learning objects are no exception. Thus, in this article we present a proposal for a Learning Objects Model for Online Learning (LOMOLEHEA) based on the European Higher Education Area, which allows the implementation of the different levels of a learning object. We demonstrate that the use of an online courses content structure, favors the creation of learning objects with in didactic units, which in turn improves organization in so far as it is highly reusable. Therefore, it is important for teachers to be familiar with the use of structures or templates that support the use of didactic units and give a uniform pattern to the contents in learning management systems.

Quixote: supporting group decisions through the web

We describe a web-based architecture to support participation in group decision making. Emphasis is placed on security aspects related with our architecture, designed to enhance trust on the system.