Lazy learning in radial basis neural networks: A way of achieving more accurate models

Radial Basis Neural Networks have been successfully used in a large number of applications having in its rapid convergence time one of its most important advantages. However, the level of generalization is usually poor and very dependent on the quality of the training data because some of the training patterns can be redundant or irrelevant. In this paper, we present a learning method that automatically selects the training patterns more appropriate to the new sample to be approximated. This training method follows a lazy learning strategy, in the sense that it builds approximations centered around the novel sample. The proposed method has been applied to three different domains an artificial regression problem and two time series prediction problems. Results have been compared to standard training method using the complete training data set and the new method shows better generalization abilities.Publicad

How the selection of training patterns can improve the generalization capability in Radial Basis Neural Networks

It has been shown that the selection of the most similar training patterns to generalize a new sample can improve the generalization capability of Radial Basis Neural Networks. In previous works, authors have proposed a learning method that automatically selects the most appropriate training patterns for the new sample to be predicted. However, the amount of selected patterns or the neighborhood choice around the new sample might influence in the generalization accuracy. In addition, that neighborhood must be established according to the dimensionality of the input patterns. This work handles these aspects and presents an extension of a previous work of the authors in order to take those subjects into account. A real time-series prediction problem has been chosen in order to validate the selective learning method for a n-dimensional problem.Publicad

Time series forecasting by means of evolutionary algorithms

IEEE International Parallel and Distributed Processing Symposium. Long Beach, CA, 26-30 March 2007Many physical and artificial phenomena can be described by time series. The prediction of such phenomenon could be as complex as interesting. There are many time series forecasting methods, but most of them only look for general rules to predict the whole series. The main problem is that time series usually have local behaviours that don't allow forecasting the time series by general rules. In this paper, a new method for finding local prediction rules is presented. Those local prediction rules can attain a better general prediction accuracy. The method presented in this paper is based on the evolution of a rule system encoded following a Michigan approach. For testing this method, several time series domains have been used: a widely known artificial one, the Mackey-Glass time series, and two real world ones, the Venice Lagon and the sunspot time series

A selective learning method to improve the generalization of multilayer feedforward neural networks.

Multilayer feedforward neural networks with backpropagation algorithm have been used successfully in many applications. However, the level of generalization is heavily dependent on the quality of the training data. That is, some of the training patterns can be redundant or irrelevant. It has been shown that with careful dynamic selection of training patterns, better generalization performance may be obtained. Nevertheless, generalization is carried out independently of the novel patterns to be approximated. In this paper, we present a learning method that automatically selects the training patterns more appropriate to the new sample to be predicted. This training method follows a lazy learning strategy, in the sense that it builds approximations centered around the novel sample. The proposed method has been applied to three different domains: two artificial approximation problems and a real time series prediction problem. Results have been compared to standard backpropagation using the complete training data set and the new method shows better generalization abilities.Publicad

A first attempt at constructing genetic programming expressions for EEG classification

Proceeding of: 15th International Conference on Artificial Neural Networks ICANN 2005, Poland, 11-15 September, 2005In BCI (Brain Computer Interface) research, the classification of EEG signals is a domain where raw data has to undergo some preprocessing, so that the right attributes for classification are obtained. Several transformational techniques have been used for this purpose: Principal Component Analysis, the Adaptive Autoregressive Model, FFT or Wavelet Transforms, etc. However, it would be useful to automatically build significant attributes appropriate for each particular problem. In this paper, we use Genetic Programming to evolve projections that translate EEG data into a new vectorial space (coordinates of this space being the new attributes), where projected data can be more easily classified. Although our method is applied here in a straightforward way to check for feasibility, it has achieved reasonable classification results that are comparable to those obtained by other state of the art algorithms. In the future, we expect that by choosing carefully primitive functions, Genetic Programming will be able to give original results that cannot be matched by other machine learning classification algorithms.Publicad

New constraints on a triaxial model of the Galaxy

We determine the values of parameters of an N-body model for the Galaxy developed by Fux via comparison with an unbiased, homogeneous sample of OH/IR stars. Via Monte-Carlo simulation, we find the plausibilities of the best-fitting models, as well as their errors. The parameters that are constrained best by these projected data are the total mass of the model and the viewing angle of the central Bar, although the distribution of the latter has multiple maxima. The best model has a viewing angle of 44 degrees, semi-major axis of 2.5 kpc, a bar mass of 1.7E10 solar masses and a tangential velocity of the local standard of rest of 171 km/s . We argue that the lower values that are commonly found from stellar data for the viewing angle (around 25 degrees) arise when too few coordinates are available, when the longitude range is too narrow or when low latitudes are excluded from the fit. The new constraints on the viewing angle of the galactic Bar from stellar line-of-sight velocities decrease further the ability of the Bar's distribution to account for the observed micro-lensing optical depth toward Baade's window : our model reproduces only half the observed value. The signal of triaxiality diminishes quickly with increasing latitude, fading within approximately one scaleheight. This suggests that Baade's window is not a very appropriate region to sample Bar properties.Comment: 10 pages, 8 figures, TeX, accepted for publication in MNRA

¿Cuáles son las emociones que expresan los alumnos y alumnas de Bachillerato, derivadas de la Literatura?

Esta es una investigación que tiene como objetivo poner de manifiesto las emociones que los chicos y chicas de Bachillerato expresan mediante la lectura de obras literarias que han leído a lo largo de los dos cursos de Bachillerato. La investigación que sepresenta fue realizada a lo largo del curso 2014/15 en el Instituto Las Viñas de Santa Coloma de Gramenet. Las técnicas de recogida de datos y análisis pertenecen al estudio cualitativo de la realidad. Los datos recogidos se basan en la participación de los y lasadolescentes, estudiantes Bachillerato. En esta investigación nos hemos acercado a las opiniones de los alumnos y alumnas de Bachillerato y les hemos preguntado sobre las emociones que han experimentado en las lecturas realizadas a lo largo de primer ysegundo curso de Bachillerato. Este fue un trabajo para el Master Arte y Humanidades de la UOC en la asignatura de Metodología de la Ciencias Humanas del curso 2014/2015.This is a research that aims to highlight the emotions expressed by high school students by Reading literary Works made in the last two academic years. Theresearch presented was carried out during the 2014/15 academic year at "Institute Les Vinyes" in the city of Santa Coloma de Gramenet (Barcelona). We used qualitative research techniques to collect data. The participation of high school students has allowed us to collect data through its opinions. In this research, we approach the emotions that high-school students have expressed and experienced by the readings were performed during the first and second year of highschool. This was a work of the Master of Arts and Humanities at the UOC course Methodology of Humanities 2014/2015

Cuáles son las emociones que surgen y/o se incrementan mediante el trabajo colaborativo con el recurso de la pizarra digital en Educación Secundaria

Se parte de la experiencia de las ponentes en la implementación del trabajo colaborativo que utiliza el recurso de la pizarra digital en el aula. A través de entrevistas a psicólogas que trabajan en diferentes EAPs de la periferia de Barcelona y a profesores/as de Secundaria se definen unos indicadores que nos permitirán definir los elementos emocionales que se dan en la ZDP (Zona de Desarrollo Próximo) de Vigotsky mediante el uso de la pizarra digital en el trabajo colaborativo en el aula. Basamos este trabajo en las teorías de Vigotsky para ir un poco más allá y situar la ZDP en el terreno emocional, describiendo en trabajo colaborativo como una interacción entre iguales. Las teorías del aprendizaje de Paulo Freire permiten fundamentar el trabajo de investigación que se plantea a los grupos de alumnos/as y las teorías Michael Cole & Silvia Scribner nos permiten situar el trabajo colaborativo en el ámbito de las capacidades a desarrollar, las llamadas habilidades comunicativas.The present research is based on the experience of the lecturers in the implementation of collaborative work that uses the resource of the digital whiteboard in the classroom. Through interviews with psychologists working in different EAPs on the outskirts of Barcelona and high school teachers, some indicators have been determined that will allow us to define the emotional elements that occur in the ZPD (Zone of Proximal Development) by Vygotsky through the collaborative work with the digital whiteboard in the classroom. We base this work on the theories of Vygotsky to go a little further and put the ZPD in the emotional field, describing in collaborative work as a peer interaction. According to the learning theories of Paulo Freire we propose this research. Moreover, Michael Cole & Sylvia Scribner theories enable us to situate the collaborative work in the area of skills to develop: the communicative skills