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 ...

In a supervised classification problem, when the vectors of data are direction- al, it means, that they take values on a k-dimensional sphere, the application of the algorithms of pattern recognition as k-nearest-neighbour ...

A Bayesian network is a compact representation of joint probability function. Formally, a Bayesian network is an acyclic directed graph in which each node represents a random variable and the relationships of dependence ...

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 ...

Over the last decades, due to the advances in information technologies, both the industrial and scientific communities have acquired large volumes of data in digital form. Most of these data sets are stored using relational ...

The development of technologies such as microarrays has generated a large amount of data. The main characteristic of this kind of data it is the large number of predictors (genes) and few observations (experiments). Thus, ...

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 ...

Clustering may be defined as a process that aims to find partitions of similar objects. It is an unsupervised recognition procedure since there are no predefined classes that indicate grouping properties in the data set. ...

Support Vector Machines (SVM) is a new technique of classification that has received much attention in recent years. In many applications, the SVM has shown better performance than machine learning methods, and it has been ...