In this thesis, a data preprocessing environment has been created, for use in a supervised classification context, with the Windows platform of the R programming language and environment for statistical computing and ...

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 ...

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 technology of microarrays introduced in the middle of the nineties allow the analysis of the gene expression levels of thousands of genes simultaneously. The identification of genes with an expression level very different ...

The automatic extraction of knowledge from very large document collections is becoming an important issue in order to exploit the increasing available information stored in text form. A significant aspect of this extraction ...

The gene expression data obtained through the technology of microarrays are characterized by its considerably greater amount of features in comparison to the number of observations. The direct use of traditional statistics ...

Logistic regression analysis is used in classification to find out which group an individual belong from a predictor variables set. In classification sometimes we work with data sets with more variables than observations. ...

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 ...