Asociación Española Para La Inteligencia Artificial España Time Series Classification by Boosting Interval Based Literals *

Cluster analysis of genetic algorithms results

Asociación Española para la Inteligencia Artificial España Adamska, Katarzyna Cluster analysis of genetic algorithm results Non-profit academic project, developed under the open access initiativé

Time Series Classification by Boosting Interval Based Literals

A supervised classification method for temporal series, even multivariate, is presented. It is based on boosting very simple classifiers: clauses with one literal in the body. The background predicates are based on temporal intervals. Two types of predicates are used: i) relative predicates, such as “increases” and “stays”, and ii) region predicates, such as “always” and “sometime”, which opera...

Resumen de la XI Conferencia de la Asociacion Española para la Inteligencia Artificial (CAEPIA 2005)

Support Vector Machines of Interval-based Features for Time Series Classification

In previous works, a time series classification system has been presented. It is based on boosting very simple classifiers, formed only by one literal. The used literals are based on temporal intervals. The obtained classifiers were simply a linear combination of literals, so it is natural to expect some improvements in the results if those literals were combined in more complex ways. In this w...

Utilización de redes neuronales en la caracterización, modelación y predicción de series temporales económicas en un entorno complejo

En el presente trabajo se realiza una revisión de las principales implicaciones del nuevo enfoque de la complejidad, y de sus relaciones con la no linealidad y la teoría del caos para el estudio de los problemas económicos. En particular, se analiza la incidencia del cambio de enfoque en el análisis de series temporales económicas, haciendo especial hincapié en la aplicación de la metodología d...