FERRER TROYANO , Francisco Javier

Mixed Zr–Si oxide thin films have been prepared at room temperature by ion beam decomposition of organometallic volatile precursors. The films were flat and amorphous. They did not present phase segregation of the pure single oxides. A significant amount of impurities (–C–, –CHx, –OH, and other radicals coming from partially decomposed...

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En este capítulo se describen diversas técnicas de Minería de Datos que muestran la utilidad de las mismas para la extracción de conocimiento en proyectos de desarrollo del Software. En concreto, se describen las tres fases centrales del proceso: el preprocesado de los datos, mediante la selección de los atributos más relevantes; la Minería de...

Mixed oxides ZrxSi1−xO2 (0bxb1) thin films have been prepared at room temperature by decomposition of (CH3CH2O)3SiH and Zr[OC (CH3)3]4 volatile precursors induced by mixtures of O2 + and Ar+ ions. The films were flat and amorphous independently of the Si/Zr ratio and did not present phase segregation of the pure single oxides (SiO2 and ZrO2). A...

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Visualization techniques provide an outstanding role in KDD process for data analysis and mining. However, one image does not always convey successfully the inherent information from high dimensionality, very large databases. In this paper we introduce VSIS (Visual Set of Information Segments), an interactive tool to visually explore...

Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper describes a classification system based on decision rules that may store up-to-date border examples to avoid unnecessary revisions when virtual drifts are present in data. Consistent rules classify new test examples by...

Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper describes a classification system based on decision rules that may store up–to–date border examples to avoid unnecessary revisions when virtual drifts are present in data. Consistent rules classify new test examples by...

Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper describes a classification system based on decision rules that may store up--to--date border examples to avoid unnecessary revisions when virtual drifts are present in data. Consistent rules classify new test examples by...

This paper presents a scalable learning algorithm to classify numerical, low dimensionality, high-cardinality, time-changing data streams. Our approach, named SCALLOP, provides a set of decision rules on demand which improves its simplicity and helpfulness for the user. SCALLOP updates the knowledge model every time a new example is read,...

As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if it is possible to find a good value of the parmeter k for each example according to their attribute values. Or at least, if there is a pattern for the parameter k in the original search space. We have carried out different...

Visualization has become an essential support throughout the KDD process in order to extract hidden information from huge amount of data. Visual data exploration techniques provide the user with graphic views or metaphors that represent potential patterns and data relationships. However, an only image does not always convey high–dimensional...

Great organizations collect open-ended and time-changing data received at a high speed. The possibility of extracting useful knowledge from these potentially infinite databases is a new challenge in Data Mining. In this paper we propose an anytime incremental learning algorithm for mining numeric data streams. Within Supervised Learning, our...

This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Supervised Learning field, our approach, named SCALLOP, provides a set of decision rules whose size is very near to the number of concepts to be extracted. Experimental results...

The k-Nearest Neighbor algorithm (k-NN) uses a classification criterion that depends on the parameter k. Usually, the value of this parameter must be determined by the user. In this paper we present an algorithm based on the NN technique that does not take the value of k from the user. Our approach evaluates values of k that classified the...

One of the problems found in generic project databases, where the data is collected from different organizations, is the large disparity of its instances. In this chapter, we characterize the database selecting both attributes and instances so that project managers can have a better global vision of the data they manage. To achieve that, we...

This paper presents an empirical study analysing the relationship between a set of metrics for Fourth–Generation Languages (4GL) programs and their maintainability. An analysis has been made using historical data of several industrial projects and three different approaches: the first one relates metrics and maintainability based on techniques...

En este artículo presentamos FACIL, un algoritmo de aprendizaje incremental dirigido a la clasificación de data streams numéricos. Mediante un esquema de ventana múltiple y una política de generalización moderada, nuestra propuesta genera reglas de decisión cuya inconsistencia es controlada mediante ejemplos internos que indican las variaciones...

We have studied low refractive index fluorine doped silica thin films prepared by reactive magnetron sputtering. Two experimental parameters were varied to increase the porosity of the films, the geometry of the deposition process (i.e., the use of glancing angle deposition) and the presence of chemical etching agents (fluorine species) at the...

The application of data mining techniques to the managing of software development projects (SDP) is not an uncommon phenomenon, as in any other productive process that generates information in the way of input data and output variables. In this paper, a set of tools developed by the authors, that generate, in a visual way, managing rules...