Software engineering has traditionally focussed on functional requirements and how to build software that has few bugs and can be easily maintained. Most design approaches include...
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
— the paper discusses an approach of using traditional time series analysis, as domain knowledge, to help the data-preparation of support vector machine for classifying documents...
Ting Yu, Tony Jan, John K. Debenham, Simeon J. Sim...
Abstract. The Unpredictability Measure computation algorithm applied to psychoacoustic model-based broadband noise attenuation is discussed. A learning decision algorithm based on ...
Andrzej Czyzewski, Marek Dziubinski, Lukasz Litwic...
Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction ...