Currently there exists a great variety of methods and algorithms attempting to optimize the process of classification. However, these methods do not take into account the internal structure of the classification datasets. ...

Nowdays throw due to the continuous advance of technology, statisticians have been facing the need to develop new methods to extract meaningful information quickly and efficiently in large data sets, such as functional ...

Desde mitades del siglo XX se vienen observando fenómenos climáticos en nuestro planeta, como por ejemplo el aumento de la temperatura y el deshielo ártico, cambios en gran escala en las cantidades de precipitación y, ...

Los datos de alta dimensión y funcionales están ganando importancia en problemas de predicción debido a los avances técnicos que permiten su captura y tratamiento. Este tipo de datos aparecen frecuentemente en la Medicina ...

In the current world of science and technology the data arrive continuously over time, this type of data is called data stream and is impractical to store all of the data. The data mining and traditional techniques of ...

La estadística multivariada ofrece diversas herramientas que permiten realizar un análisis para ciertos conjuntos de datos. Sin embargo surge una rama de la estadística en la cual se dejan de observar conjuntos de datos ...

In recent years, technological advances have resulted in a huge increment in data production as in the evolution of methods that facilitated its collection. The data that arrive continuously and massively with infinite ...

Many modern applications of automatic document classification require learning accurately with little training data. Addressing the need to reduce the manual labeling process, the semi-supervised classification technique ...

Temporal datasets provide records of the evolution and dependencies of random variables over time. Recently, there has been an increase in the application of temporal datasets in areas such as intrusion detection, fraud ...