Decision Queue Classifier for Supervised Learning Using Rotated Hyperboxes

This article describes a new system for learning rules using rotated hyperboxes as individuals of a genetic algorithm (GA). Our method attempts to find out hyperboxes at any orientation by combining deterministic hill-climbing with GA. Standard techniques, such as C4.5, use hyperboxes that are aligned with the coordinate axes. The system uses the decision queue (DQ) as method of representing the rule set. It means that the obtained rules must be applied in specific order, that is, an example will be classify by the i-rule only if it doesn’t satisfy the condition part of the i-1 previous rules. With this policy, the number of rules is less because the rules could be one inside of another one. We have tested our system on real data from UCI repository. Moreover, we have designed some two-dimensional artificial databases to show graphically the experiments. The results are summarized in the last section

Data Set Editing by Ordered Projection

This paper presents a new approach to data set editing. The algorithm (EOP: Editing by Ordered Projection) has some interesting characteristics: important reduction of the number of examples from the database; lower computational cost (O(mn log n)) with respect to other typical algorithms due to the absence of distance calculations; conservation of the decision boundaries, especially from the point of view of the application of axis-parallel classifiers. The performance of EOP is analysed in two ways: percentage of reduction and classification. EOP has been compared to IB2, ENN and SHRINK concerning the percentage of reduction and the computational cost. In addition, we have analysed the accuracy of k-NN and C4.5 after applying the reduction techniques. An extensive empirical study using databases with continuous attributes from the UCI repository shows that EOP is a valuable preprocessing method for the later application of any axis-parallel learning algorithm.Comisión Interministerial de Ciencia y Tecnología TIC2001-1143-C03-0

Searching for similar semiqualitative temporal patterns in time-series databases

A way to obtain behaviour patterns of semiqualitative models of dynamic systems automatically is proposed in this paper. The temporal evolution of these models is stored into a database. This is a time series database. This database may be obtained as is explained in [Ortega et al . 1999] or by means of sensor data. In any way, the database contains the values of state variables and parameters. Searching for similar patterns in such database is essential, because it helps in predictions, hypothesis testing and, in general, in data mining and rule discovery. A language to carry out queries about the qualitative and temporal properties of this time-series database is also proposed. This language allows us to study all the states of a dynamic system: the stationary and the transient states. The language is also intended to classify the different qualitative behaviours of our model. This classification may be carried out according to a specific criterion or automatically by means of clustering algorithms. The semiqualitative behaviour of a system is expressed by means of hierarchical rules obtained by means of machine learning algorithms. The methodology is applied to a logistics growth model with a delay.Ministerio de Ciencia y Tecnología TIC98-1635-

Semiqualitative Methodology to Reasoning about Dynamic Systems

En este artículo se propone una metodología para razonar sobre los modelos semicualitativos construidos para sistemas dinámicos con conocimiento cualitativo y cuantitativo. La información cualitativa de estos sistemas puede componerse de: operadores cualitativos, etiquetas cualitativas, funciones de bandas y funciones continuas cualitativas. Se presenta un formalismo para incorporar esta información a los modelos. La metodología propuesta permite estudiar no sólo del régimen estacionario, ampliamente estudiado en la literatura, sino que además posibilita realizar un estudio del régimen transitorio de los sistemas. Se presenta también un estudio teórico sobre la validez de las conclusiones obtenidas la metodología. Los comportamientos del sistema se pueden obtener automáticamente aplicando algoritmos de clustering y se expresan mediante un conjunto de reglas jerárquicas obtenidas mediante algoritmos genéticos. La metodología se ha aplicado a un par de modelos, siendo uno el modelo de dos estanques interconectados y otro un modelo de crecimiento logístico donde se ha incorporado un retraso en el bucle de realimentación.In this article a methodology to reason over semiqualitative models built for dinamic systems with qualitative and quantitative knowledge is proposed. The qualitative information of these systems can be composed of: qualitative operators, qualitative labels, bands functions and qualitative continuous functions. A formalism to incorporate this information to the models is presented. The proposed methodology allows to study not just about the stationary regime, widely studied in the literature, but also it makes possible to carry out a study of the transitory regime of the systems. It also presents a theoretical study about the validity of the conclusions obtained in the methodology. The behaviours of the system can be obtained automatically applying clustering algorithms and are expressed through a set of hierarchical rules obtained from genetics algorithms. The methodology has been applied to a couple of models, one of them is the interconnected pools model and the other a logistical growing model where a delay in the feedback curls has been incorporated

Efficient Learning Machines

Computer scienc

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design